Welcoming the Grainite Team to MongoDB: Accelerating Atlas Stream Processing
Tens of thousands of customers and millions of developers rely on MongoDB Atlas to run business-critical applications because of its flexible document data model and ability to work with virtually any type of data using a single, intuitive developer data platform that can run on all major cloud providers. Earlier this year, we announced that we would enable developers to apply the benefits of the document model and a unified interface to streaming data with Atlas Stream Processing . In a short amount of time, we have seen a strong response from developers eager to use this capability to simplify building event-driven applications. To accelerate the development of our streaming offering, we are thrilled to announce that the team behind Grainite — a streaming application platform, backed by Sequoia Capital and Menlo Ventures, that makes it easy to read, process, store, and query events in real-time — has now joined MongoDB. Grainite was founded by world-class technologists Ashish Kumar, who spent over ten years running structured storage products and other high-scale infrastructure projects at Google, and Abhishek Chauhan, who previously served as CTO of Cloud Networking at Citrix. Ashish and Abhishek bring with them a team of talented engineers to MongoDB who will help accelerate the development of Atlas Stream Processing and the release of new capabilities that will make it even easier for customers to process and analyze streaming data for real-time application experiences. “We’re excited to be joining a company that shares our vision for making it effortless to build event-driven applications,” said Kumar. “We’re looking forward to continuing to develop a world-class streaming platform that will make it easier for developers to incorporate real-time data into their applications and becoming part of an organization that can significantly amplify the reach and impact of event-driven applications for developers and end users.” We look forward to welcoming the Grainite team to MongoDB and sharing updates on Atlas Stream Processing and our broader streaming roadmap in the near future.
Congratulations to the 2023 APAC Innovation Award Winners
I’m thrilled to announce the nine winners of the 2023 MongoDB APAC Innovation Awards . The MongoDB Innovation Awards honor projects and people who dream big. They celebrate the groundbreaking use of data to build compelling applications and the creativity of professionals expanding the limits of technology with MongoDB. This year, we have broken the awards down regionally to celebrate organizations in APAC, from startups to industry-leading enterprises, across a wide variety of industries, who are delivering big results. We are delighted to announce the winners below: 2023 MongoDB APAC Innovation Award Winners: Positive Impact Open Government Products Open Government Products (OGP) is an in-house team of engineers, designers, and product managers, who is a part of the Singapore Government, and is responsible for building technologies for the public good. OGP used MongoDB’s developer data platform, MongoDB Atlas to create its digital form builder, FormSG. Used by the Singapore government and public healthcare institutions, FormSG securely collects data from residents and businesses and helps public officers to create digital government forms in minutes. It eliminates the use of paper forms and the manual process of transcribing physical documents, which had raised concerns around data privacy and protection. During the pandemic, FormSG enabled public officers to collect more than 100,000 daily temperature declarations nationwide. Today, FormSG has served more than 120,000 public officers from 155 agencies and it has created more than 500,000 digital forms to help the government collect data on travel and health declarations by visitors to the country, applications for COVID-19 swab tests, and applications for financial assistance. Organization Transformation Bendigo and Adelaide Bank Bendigo and Adelaide Bank is one of Australia’s largest banks, with around 7,000 employees helping more than 2.2 million customers achieve their financial goals. The bank has been on a multi-year journey of transformation using MongoDB's developer data platform to improve efficiency and deliver a better customer experience as they fulfill their vision to become Australia’s bank of choice. Recently, the cloud team launched Ready-Set-MongoDB (or RSM). This event-driven framework allows developers to streamline the consumption of internal or external APIs, and applies data transformations and storage automatically within a MongoDB collection of their choice. Using MongoDB Atlas Search, the bank also enabled developers to gain insights across its multi-cloud deployments, identifying cost savings, and providing inventory information to account owners and technical stakeholders. Within the first 18 months of launching these programmes, the automation had saved the organization more than 1,100 developers days. It also helped reduce human involvement, removed stale data, and allowed engineers to focus on the things that matter. The development of Ready-Set-MongoDB is ongoing and improving, as new Bendigo multi-cloud challenges arise and new MongoDB products are released. The application is a perfect representation of how Bendigo's Technology Department is using modern technology, rapid development, and innovation-led problem solving to drive organizational transformation. Heroes in Health Redcliffe Lifetech Private Limited Over the last few years, Redcliffe Labs has become India's fastest growing technology-driven diagnostics service provider. Redcliffe Labs is on a mission to serve 500 Million Indians by 2030 with fusion of technology and world- class laboratories. The company already serves thousands of people daily, with more than 73 labs and close to 1500 walk-in centers across 180 cities. Redcliffe Labs has relied on MongoDB Atlas’ flexible document model to power its innovative Smart Health Report, a patient resource that provides a number of indicators and trackers to gauge holistic health. The MongoDB developer data platform's best in class security, compliance, and privacy controls allows Redcliffe's team to confidently handle even the most sensitive patient data. MongoDB Atlas takes care of many of the traditional database management challenges, which means that developers can spend their time building diagnostics for patients, rather than managing databases. Redcliffe Labs is focusing on incorporating next-generation technologies in the diagnostics space with an AI platform that will make Interactive Diagnostics reports, Advanced Health Profiling and more detailed Diagnostics and Health Alerts. Industry Disruptor Cathay Pacific Cathay Pacific , Hong Kong’s home carrier operating in more than 60 destinations worldwide, has been on an impressive journey to become one of the very first airlines to create a truly paperless flight deck. Until recently, a flight from Hong Kong to New York would require a crew to review more than 150 pages of finely printed text and charts before their flight and make ongoing updates throughout the trip. In 2019, Cathay Pacific conducted the first zero paper flight, removing 50kg of manuals, charts, maps, and flight briefing paperwork. They achieved this enormous feat with the help of one seamless and highly customized iPad application: Flight Folder. Built on MongoDB Atlas, Flight Folder is designed to improve the pilot briefing experience. MongoDB helped consolidate dozens of different information sources into one place, and made it possible for flight crews to easily share their experiences with others. It also included a digital refueling feature that helps crews become much more efficient with fueling strategies – saving significant flight time and costs. The use of MongoDB Device Sync enables seamless syncing and no data loss even when the app goes on- and offline mid-flight. Since the Flight Folder launch, Cathay Pacific has completed more than 340,000 flights with full digital integration in the flight deck. In addition to the greatly improved flight crew experience, flight times have been reduced, and digital refueling saves eight minutes of ground time on average. All these efficiencies have helped the company avoid the release of 15,000 tons of carbon. From Batch to Real-Time Adani Digital Labs Adani Digital Labs is the India-based digital innovation arm of the larger Adani group. The lab’s team's mission is to create one single platform – a SuperApp called AdaniOne – to empower a billion stories in India. To address several use cases and the huge scale that will be required by the superapp, the Adani Digital team selected MongoDB Atlas as its the main transactional database that will further enhance the application. A key component of the app is how it can bring together disparate data in order to provide a single view of activity across the application. In the first process, developers had taken out the data in batches and sent it to their database However, this was too slow and unpredictable as far as business requirements are concerned. Also, the consolidated view of customer history, orders, inventory, and supply chain network updates was likely to impact their customer's ability to generate revenue. Therefore, in order to find a better solution, Adani Digital Labs built a more modern architecture in line with MongoDB. Using MongoDB's Change Streams and the data platform's native Kafka connector, they created an event-based architecture that pushes the data out in real-time for analysis. Adani Digital Labs is still in the early phases of the SuperApp's rollout and collaborating with MongoDB as its developer data platform continues to help the firm to grow and deliver insights in real time. Industry 4.0 Dongwha Founded in 1948, the Dongwha Group has evolved from a singular focus on the wood and timber industry into a global leader across a number of sectors including building materials, chemicals and media. As part of its wider digital transformation strategy, Dongwha required smarter factories that would improve and optimize their production efficiency. Dongwha built an innovative Smart Factory Software platform that collects and analyzes data to enhance quality and production management capabilities. Originally, the platform was built with the community version of MongoDB. However, in order to scale and adapt, the team recently migrated to MongoDB Atlas in the cloud. This enabled them to store large volumes in the fastest and most secure way, optimize their solution for time series data, and make it easy to run machine learning across their data. Dongwha completed the migration seamlessly, without any disruption or downtime to their factories, and it has now been launched across five different sites. Over the last year, the application has significantly increased its availability and reliability while performance has improved by as much as 6x . As they look to the future, Dongwha plans to roll out the software to more of its international factories. Digital Native myBillBook India is home to more than 60 million small and medium-sized businesses (SMBs) but only a small portion of those SMBs are taking advantage of digitization and many still operate using pen and paper. In addition, many businesses in India still struggle with fluctuations in internet services, outages, and latency. FloBiz is on a mission to change that with myBillBook , a one-stop solution that helps SMBs create professional invoices, manage stock, collect payments, automate reminders through smart banking, engage with their customers, manage staff attendance and payroll and generate more than 25 business reports for accounting and decision making. The app is also mobile-first, so businesses can access them from their mobile devices and allows users to manage billing and inventory in both online and offline environments. The myBillbook app is powered by MongoDB Atlas, providing the flexible and scalable foundation for the business to do everything from building new features to performing complex analytical queries. In addition, Realm, MongoDB’s mobile database, with Atlas Device Sync, supports offline usage and automatic syncing with the cloud to ensure there is never data or functionality loss for users due to poor internet connection. Because of its success in supporting customers with business critical operations, more than 6.5 million business owners in India are now using myBillbook for their billing, accounting, collection and business growth. Customer Focused KASIKORN Business-Technology Group Established in 1945, Kasikornbank (KBank) is one of the largest and oldest banks in Thailand. Their mission is to strive towards service excellence and empower every customer’s life and business. One of KBank’s subsidiaries, KASIKORN Business-Technology Group (KBTG) , developed a mobile banking application – MAKE by KBank. MongoDB Atlas’ flexibility and ease of development enabled MAKE’s development team to choose the best type of database for its tasks, to automate data tiering with Atlas Online Archive, and to reduce hours spent on operational maintenance. With more time to focus on delivering new innovations to customers, they created unique features like Cloud Pocket which can allocate funds into unlimited customizable pockets for separate usage. They also built Pop Pay, a feature that allows users to easily search for nearby friends and transfer money by clicking their profile picture as well as “Expense Summary" a spending analysis services that helps inform and manage users’ financial habits. As of January 2023, MAKE has acquired more than 1 million users, and increased the number of transactions in MAKE from 900,000 to more than 7.5 million in a span of one year. Massive Scale China Mobile China Mobile provides mobile voice and multimedia services via its nationwide mobile telecommunications network across mainland China and Hong Kong. It is the world's largest mobile network operator by total number of subscribers. The telecommunications leader is using MongoDB to support one of its largest and most critical push services, which sends out billing details to more than 1 billion users every month. Prior to MongoDB, the tech team relied on Oracle, but as the user numbers increased, performance degraded. Despite large investments, it was still taking too long to do basic requests like finalize and deliver bills to users. In 2019, after comprehensive testing, China Mobile migrated to MongoDB. By taking advantage of MongoDB's native sharding, they were able to improve performance by 80% and go from 50 Oracle machines, to just 12 machines for the same workload. The service now handles all current requirements and is set up to scale with future growth. With the support of MongoDB, China Mobile is growing steadily,with more than 168 million monthly users and has one of the highest customer satisfaction scores in the China Mobile group.
2023 APAC Innovation Award 수상자 축하 메시지
드디어 2023 MongoDB APAC Innovation Awards 에 선정된 9명의 수상자를 발표하게 되었습니다. MongoDB Innovation Award는 큰 꿈을 가진 기업인과 프로젝트에게 수여되는 상으로, 데이터를 획기적인 방식으로 활용하여 우수한 애플리케이션을 구축하고 MongoDB를 통해 기술의 한계를 넓힌 전문가들의 창의력을 치하합니다. 다양한 산업 부문에 걸쳐 스타트업에서부터 업계를 선도하는 기업에 이르기까지 원대한 포부를 갖고 큰 성과를 거둔 아시아 태평양 지역의 기업들을 치하하기 위해 올해에는 수상 부문을 지역별로 세분화하였습니다. 수상자는 아래와 같습니다. MongoDB APAC Innovation Award 수상자: Positive Impact Award 부문 Open Government Products OGP(Open Government Products) 는 싱가포르 정부 소속으로 공익을 위한 기술 개발을 담당하고 있는 엔지니어와 설계자 및 제품 관리자로 구성된 내부 개발 팀입니다. OGP는 MongoDB의 개발자 데이터 플랫폼인 MongoDB Atlas를 이용해 FormSG라는 디지털 서식 빌더를 개발했습니다. 싱가포르 정부와 공공 의료 기관에서 사용되고 있는 FormSG는 주민과 기업의 데이터를 안전하게 수집하여 공무원이 디지털 정부 서식을 몇 분 만에 작성할 수 있도록 지원하는 소프트웨어입니다. FormSG를 사용하면 데이터를 서류 양식을 일일이 수동으로 작성할 필요가 없기 때문에 개인정보 및 보호에 관한 우려가 해소됩니다. 팬데믹 기간 동안 공무원들은 FormSG를 사용해 전국의 일일 기온 정보를 십만 건 이상 수집할 수 있었습니다. 현재까지 155곳의 기관에서 12만 명 이상의 공무원들이 FormSG를 이용해 50만 개 이상의 디지털 서식을 작성하였으며, 이를 통해 싱가포르 정부는 자국에 입국하는 방문객들의 여행 및 건강 정보와 COVID19 검사 및 재정 지원 신청에 관한 자료를 수집할 수 있었습니다. Organizational Transformation 부문 Bendigo and Adelaide Bank Bendigo and Adelaide Bank 는 호주에서 가장 큰 은행 중 하나로 7천여 명의 직원을 보유하고 있으며, 220만 명 이상의 고객이 재무 목표를 달성할 수 있도록 지원하고 있습니다. 이 은행은 호주의 대표 은행으로 거듭난다는 사명 하에 MongoDB의 개발자 데이터 플랫폼을 이용해 효율성을 높이고 더 나은 고객 경험을 선사하기 위한 다년 간의 혁신 여정을 진행 중입니다. 최근 이 은행의 클라우드 담당 팀에서는 Ready-Set-MongoDB(RSM)를 출시했습니다. 이벤트 중심의 이 프레임워크를 통해 개발자는 내/외부 API의 소비를 간소화하고 원하는 MongoDB 컬렉션 내에 데이터 변환 및 저장을 자동으로 적용할 수 있습니다. 이 은행은 MongoDB Atlas Search를 사용하여 개발자들이 자사의 멀티 클라우드 배포 환경에 대한 인사이트를 확보하고 비용 절감 여부를 식별하며 계정 소유자와 기술 이해 관계자들에게 목록 정보를 제공하도록 지원했습니다. 이들 프로그램을 시작한 후 첫 18개월 동안 자동화 덕분에 개발자의 업무 시간이 1,100일이나 줄어들었습니다. 또한 인적 개입이 줄어들고 오래된 데이터가 사라졌으며 엔지니어가 중요한 업무에 매진할 수 있게 되었습니다. Bendigo 멀티 클라우드의 새로운 과제가 등장하고 MongoDB 신제품이 출시됨에 따라 현재 Ready-Set-MongoDB를 개발 중이며 성능을 개선 중입니다. Ready-Set-MongoDB는 Bendigo의 기술 부서가 최신 기술 활용과 빠른 개발 및 혁신 기반의 문제 해결을 통해 조직의 혁신을 도모하는 과정을 잘 보여주는 애플리케이션입니다. Heroes in Health Award 부문 Redcliffe Lifetech Private Limited Redcliffe Labs 는 지난 몇 년 간 인도에서 가장 빠르게 성장한 기술 중심 진단 서비스 업체로 성장했습니다. Redcliffe Labs는 기술과 세계 정상급 실험실을 융합하여 2030년까지 5억 명의 인도인에게 서비스를 제공한다는 사명감을 갖고 있습니다. 이 회사는 현재 180 개 도시에 걸쳐 73 곳 이상의 실험실과 1,500여 개의 워크인 센터에서 매일 수천 명의 사람들에게 진단 서비스를 제공하고 있습니다. Redcliffe Labs는 MongoDB Atlas의 유연한 문서 모델을 이용해 자사의 혁신적인 Smart Health Report를 실행하고 있습니다. 이 Report는 다수의 지표와 추적기로 전반적인 건강 상태를 측정할 수 있도록 지원하는 환자 리소스입니다. 동급 최고의 보안과 컴플라이언스 및 프라이버시 제어를 제공하는 MongoDB 개발자 데이터 플랫폼 덕분에 Redcliffe 개발 팀은 가장 중요한 환자 데이터까지도 자신 있게 처리할 수 있게 되었습니다. MongoDB Atlas가 기존의 데이터베이스 관리 문제를 대다수 해결해주기 때문에 개발자가 데이터베이스 관리 대신, 환자 진단 시스템을 구축하는 데 집중할 수 있습니다. Redcliffe Labs는 AI 플랫폼을 통해 진단 영역에 차세대 기술을 통합하여 대화형 진단 보고서와 고급 건강 프로파일링 및 보다 상세한 진단 및 건강 알림 시스템을 개발하는 데 주력하고 있습니다. Industry Disruptor Award 부문 Cathay Pacific 전 세계 60 개 이상의 취항지를 운항하고 있는 홍콩 국적기인 Cathay Pacific은 종이 서류를 일체 사용하지 않는 조종실을 보유한 최초의 항공사 중 하나로 거듭나기 위한 여정을 진행하고 있습니다. 최근까지 홍콩발 뉴욕 비행에서는 승무원이 이륙하기 전에 글자와 차트가 빼곡히 인쇄된 150 페이지 이상의 서류를 일일이 검토하여 비행 내내 정보를 계속 업데이트해야 했습니다. 2019년에 Cathay Pacific 은 처음으로 제로 페이퍼 비행 정책을 실시하여 50kg에 달하는 매뉴얼과 차트, 지도 및 비행 브리핑 문서를 없앴습니다. 이렇게 대대적인 혁신을 이룰 수 있었던 것은 고도로 커스터마이징된 아이패드 애플리케이션인 Flight Folder의 원활한 프로세스 덕분이었습니다. MongoDB Atlas에 기반한 Flight Folder는 조종사의 브리핑 경험을 개선하도록 설계되었습니다. MongoDB가 수십 개의 서로 다른 정보 소스를 한 곳에 통합해준 덕분에 승무원들이 비행 경험을 동료들과 손쉽게 공유할 수 있었습니다. 또한 디지털 급유 기능이 포함되어 있어 승무원이 급유 전략을 훨씬 효율적으로 시행하여 비행 시간과 비용을 대폭 절약할 수 있습니다. MongoDB Device Sync를 사용하면 비행 중에 앱을 원활하게 동기화할 수 있고, 오프라인 상태가 되더라도 데이터가 손실되지 않습니다. Flight Folder를 사용하기 시작한 이후로 Cathay Pacific은 조종실을 전면 디지털화하여 34만 건 이상의 비행을 무사히 마쳤습니다. 승무원의 비행 경험이 대폭 향상된 것은 물론, 비행 시간이 줄어들었고 디지털 급유 기능 덕분에 지상에서 머무르는 시간이 평균 8분가량 줄어들었습니다. 이러한 효율성을 달성하면서 Cathay Pacific은 탄소 배출량을 1만 5천 톤가량 줄일 수 있었습니다. From Batch to Real-Time 부문 Adani Digital Labs Adani Digital Labs 은 인도에 소재한 Adani 그룹의 디지털 혁신 자회사입니다. 이 회사 개발 팀의 사명은 AdaniOne이라는 이름의 슈퍼앱(SuperApp)을 단일 플랫폼 형태로 개발하여 인도 내 십억 명의 이야기를 지원하는 것입니다. 여러 가지 사용 사례와 슈퍼앱에서 이루어질 확장 문제를 해결하기 위해 Adani Digital 팀은 애플리케이션의 성능을 개산할 주요 거래 데이터베이스로 MongoDB Atlas를 선정했습니다. 이 앱의 주요 구성 요소는 애플리케이션 전반의 활동을 한 눈에 보여주기 위해 상이한 데이터를 취합하는 방법입니다. 첫 번째 프로세스에서 개발자들은 데이터를 배치로 가져와 자사의 데이터베이스에 전송했는데, 비즈니스 요구사항 측면에서 속도가 너무 느리고 예측하기 어려웠습니다. 또한 고객 이력과 주문, 목록 및 공급망 네트워크 업데이트에 관한 통합 뷰가 고객의 수익 창출 능력에 영향을 줄 가능성이 있었습니다. 따라서 더 나은 솔루션을 찾기 위해 Adani Digital Labs은 MongoDB에 걸맞는 최신 아키텍처를 구축했습니다. MongoDB의 Change Streams와 데이터 플랫폼의 네이티브 Kafka 커넥터를 이용해 분석용 데이터를 실시간으로 산출하는 이벤트 기반 아키텍처를 제작했습니다. Adani Digital Labs은 아직까지 슈퍼앱의 롤아웃 초기 단계에 있으며, 개발자 데이터 플랫폼을 통해 조직의 성장을 도모하고 인사이트를 실시간으로 제공하면서 MongoDB와 협업하고 있습니다. Industry 4.0 부문 Dongwha 1948년 설립된 동화그룹 은 목재 산업을 바탕으로 성장했으며, 건장재 등 고부가 가치 제품군으로 사업의 수직 계열화를 이루며 마켓 리더로서 공고히 자리매김했습니다. 현재는 소재는 물론 화학, 오토라이프, 미디어까지 사업 영역을 확대했습니다. 동화 그룹은 폭넓은 디지털 전환 전략의 일환으로, 자사의 생산 효율성을 개선 및 최적화할 스마트 팩토리가 필요했습니다. 이에 데이터를 수집 및 분석하여 품질과 제품 관리 기능을 개선하는 혁신적인 Smart Factory Software 플랫폼을 구축했습니다. 이 플랫폼은 본래 MongoDB 커뮤니티 버전으로 구축되었다가 확장과 조정을 위해 최근 클라우드 기반의 MongoDB Atlas로 마이그레이션했습니다. 이를 통해 대량의 데이터를 가장 빠르고 안전하게 저장할 수 있게 되었고, 솔루션을 시계열 데이터에 맞게 최적화하며, 데이터 전반에서 머신러닝을 손쉽게 실행할 수 있게 되었습니다. 동화 그룹은 다운타임 및 공장 가동 중지 없이 마이그레이션 함으로써 애플리케이션의 신뢰성과 가용성이 크게 향상되었을 뿐만 아니라 기존 AWS EC2에 직접 설치된 Single Node MongoDB 대비 데이터 조회 성능이 6배나 향상되었습니다. 동화기업은 국내 3개 사업장과 해외 2개 사업장에 스마트팩토리를 성공적으로 구현하였으며, 이러한 경험을 바탕으로 향후에는 공장 최적화를 위한 데이터 분석 영역으로 스마트 팩토리 소프트웨어를 확장해 나갈 계획입니다. Digital Native 부문 myBillBook 인도는 6천만 개 이상의 중소 기업이 모여 있는 SMB의 본고장이지만 디지털화의 이점을 누리고 있는 기업들은 이들 중 소수에 불과하며 아직도 대다수가 업무에 펜과 종이를 사용하고 있습니다. 게다가 인도에 소재한 대부분의 기업들이 여전히 인터넷 서비스와 중단 및 지연에 따른 변동에 시달리고 있습니다. FloBiz는 원스톱 솔루션인 myBillBook을 통해 이 문제를 해결한다는 사명을 안고 있습니다. myBillBook 는 SMB를 대상으로 전문 인보이스 작성, 재고 관리, 대금 회수, 스마트 뱅킹을 통한 알림 자동화, 고객과의 교류, 직원 출근 및 급여 지급 관리, 회계 처리 및 의사 결정을 위한 25개 이상의 비즈니스 보고서 생성을 지원하는 솔루션입니다. 이 앱은 모바일에 최적화된 환경이기 때문에 기업이 모바일 기기에서 액세스할 수 있고 사용자들이 온/오프라인 환경 모두에서 대금 지급과 재고를 관리할 수 있습니다. MongoDB Atlas에서 실행되는 myBillbook 앱은 새 기능 개발에서부터 복잡한 분석 쿼리 수행에 이르기까지 기업이 모든 작업을 수행할 수 있는 유연하고 확장 가능한 기반을 제공합니다. 또한 데이터 플랫폼에서 제공되는 모바일 데이터베이스인 MongoDB Realm은 오프라인 사용 및 동기화를 지원하여 인터넷 연결이 불안정한 상태에서도 데이터 손실이나 기능 저하가 발생하지 않습니다. 비즈니스 핵심 업무를 담당하는 고객을 성공적으로 지원한 결과, 현재 650만 곳의 인도 기업들이 대금 청구와 회계 처리 및 대금 회수에 myBillbook을 이용하고 있으며 비즈니스 성장을 도모하고 있습니다. Customer Focused 부문 KASIKORN Business-Technology Group 1945년에 설립된 Kasikornbank(KBank)는 태국에서 가장 오래되고 규모가 큰 은행 중 한 곳입니다. 이 은행의 사명은 서비스 우수성을 달성하고 모든 고객의 삶과 비즈니스를 지원하는 것입니다. KBank의 자회사 중 한 곳인 KASIKORN Business-Technology Group(KBTG) 은 MAKE by KBank라는 모바일 뱅킹 애플리케이션을 개발했습니다. MongoDB Atlas의 유연성과 개발 용이성 덕분에 MAKE의 개발 팀은 업무에 가장 적합한 데이터베이스를 선정하고 Atlas Online Archive를 통해 데이터 티어링을 자동화하며 운영 유지 보수 소요 시간을 절감할 수 있었습니다. 이로써 새로운 혁신 기능 개발에 집중하게 되면서 사용자 지정 가능한 무제한 포켓에 자금을 할당하여 별도로 사용할 수 있도록 지원하는 Cloud Pocket과 같은 고유한 기능을 개발하게 되었습니다. 이 외에도, 사용자가 주변에 있는 친구를 검색해 프로필 사진을 클릭하여 돈을 간편하게 송금할 수 있는 Pop Pay라는 기능을 개발하였고, 사용자의 재정 관리 습관을 알려주고 이를 관리할 수 있는 지출 분석 서비스인 "Expense Summary"를 개발했습니다. 2023년 1월을 기준으로 MAKE는 현재 백만 명 이상의 사용자를 보유하고 있으며, MAKE의 거래 건수는 일년 동안 90만 건에서 750만 건 이상으로 늘었습니다. Massive Scale 부문 China Mobile China Mobile 은 중국 본토와 홍콩 전역의 모바일 통신 네트워크를 통해 모바일 음성 및 멀티미디어 서비스를 제공하는 회사로, 총 가입자 수 기준으로 세계 최대 규모의 모바일 네트워크 사업자입니다. 통신 분야를 선도하고 있는 이 회사는 MongoDB를 이용해, 매달 10억 명 이상의 사용자에게 상세 대금 청구서를 발송하는 자사의 가장 큰 핵심 푸시 서비스 중 하나를 지원하고 있습니다. MongoDB를 도입하기 전에는 Oracle을 이용했는데, 사용자 수가 늘자 성능이 저하되는 문제가 발생했습니다. 설비에 대규모로 투자했음에도 불구하고, 대금 청구서를 작성해 사용자에게 전송하는 것과 같은 기본적인 요청을 하는 데에도 너무 오랜 시간이 걸렸습니다. 2019년에 종합 테스트를 거친 후 China Mobile은 MongoDB로 마이그레이션했습니다. MongoDB의 네이티브 샤딩 기술을 이용하자 성능이 80% 향상되었고, 50대의 Oracle 장비로 처리하던 워크로드를 단 12의 장비로 처리할 수 있게 되었습니다. 이 서비스는 현재 모든 요구사항을 처리하고 있으며 향후 규모 증가에 맞게 확장하도록 설계되어 있습니다. MongoDB의 지원 덕분에 China Mobile은 꾸준한 성장세를 이어오고 있으며, 1억 6천8백만 명의 월간 사용자를 확보하였고 China Mobile 그룹에서 고객 만족도 점수가 가장 높은 지사 중 한 곳이 되었습니다.
恭喜 2023 年 MongoDB 亞太地區創新獎得主
我很高興在此宣布 2023 年 MongoDB 亞太地區創新獎的九組優勝團隊。MongoDB 創新獎是為了表揚勇於挑戰的專案及人員，他們以前所未有的手法運用資料，建立非常實用的應用程式，而這些專業人士的創意，拓展了 MongoDB 技術的應用框架。今年比賽以區域做區分，是因為我們知道亞太地區有許多橫跨不同產業的公司，有的是新創、有的是業界領先企業，他們的共通點是勇於挑戰和創新，並努力交出更漂亮的成績單。以下是今年的創新獎得主： 2023 年 MongoDB 亞太地區創新獎得主： 正面影響 (Positive Impact) Open Government Products Open Government Products (OGP) 是新加坡政府內部的團隊，由一群工程師、設計師及產品經理組成。團隊負責為公眾福祉建構相關的技術。。OGP 使用 MongoDB 的開發者數據平台 MongoDB Atlas，建構了數位表格生成器 FormSG。新加坡政府及公共醫療單位透過使用 FormSG ，在安全的環境下，搜集民眾、店家及公司的資料，協助政府人員快速建立政府數位表單。FormSG 取代了過去可能會造成資料安全及隱私問題的紙本表單以及人工處理文件的過程。而在新冠疫情期間，因為有 FormSG，政府人員得以搜集每日超過十萬筆的全國每日體溫申報。現在有來自 155 個單位、超過 12 萬名的政府人員使用 FormSG，建立超過 50 萬份數位表單，幫助政府搜集來到新加坡的旅客的旅遊及健康申報，同時也應用在新冠肺炎檢驗和資金補助上。 組織轉型 (Organizational Transformation) Bendigo and Adelaide Bank Bendigo and Adelaide Bank 是澳洲最大的銀行之一，擁有約 7000 名員工，服務超過 220 萬位客戶，協助他們達成財務目標。班迪戈銀行目前正在執行多年的轉型計畫，透過 MongoDB 的開發者資料平台改善工作效率，滿足客戶要求，提供更好的使用體驗，以期望能成為澳洲銀行的第一選擇。 近期雲端團隊推出事件導向的架構 Ready-Set-MongoDB (RSM)，允許開發人員簡化內部或外部API的使用，並自動應用數據轉換和存儲到他們選擇的MongoDB叢集中。而有了 MongoDB Atlas Search，銀行的開發者可以從多雲部署中汲取洞見，找出可節約的成本，並提供帳戶所有人和技術資源相關資產庫存。 推出這項計劃的前 18 個月裡，自動化替組織的工程師省下了 1100 個工作天，同時也降低人工介入、移除過時資料，讓工程師可以關注在更重要的工作上。因為 Bendigo and Adelaide Bank 多雲上出現的新挑戰，而且 MongoDB 也推出了新產品，所以 Ready-Set-MongoDB 的研發仍是進行式，不斷調整及改善。這項應用可以體現班迪戈銀行資訊部門是如何應用現代技術、快速開發以及創新為導向的問題解決方法，推動組織轉型。 醫療英雄 (Heroes in Health) Redcliffe Lifetech Private Limited 在過去幾年的時間裡， Redcliffe Labs 成為印度成長最快速的科技診斷服務供應商。瑞德克利夫實驗室的願景是在 2030 年透過融合技術和具世界規模等級的實驗室，服務五億印度人。他們已經在 180 座城市設立超過 73 間實驗室，以及約 1500 間的現場掛號中心，每天服務上千名的病患。 Redcliffe Labs仰賴 MongoDB Atlas 靈活的文件模型製作創新智慧健康報告，提供病患一系列指標及追蹤方式，了解整體健康狀況。MongoDB 開發者資料平台擁有等級最高的資料安全、合規性以及隱私管理，Redcliffe 團隊得以安心處理最敏感的病患資料。 MongoDB Atlas 可以自動處理許多傳統資料庫管理上的挑戰，因此開發者不需要花太多時間在管理資料庫，而是專注在為病患建立診斷。Redcliffe Labs 專注於診斷的領域，研究如何將下一代技術整合至 AI 平台，提供病患具互動性的診斷報告、進階的健康檔案及更詳盡的診斷及健康警示。 產業改革者 (Industry Disruptor) 國泰航空 (Cathay Pacific) 國泰航空 是香港本土的航空公司，目前在全球航行超過 60 據點。這間航空公司正在努力成為第一間真正執行駕駛艙無紙化的航空公司。直到最近，一班從香港飛往紐約的班機，機組人員還需要在飛行之前，看超過 150 張印刷文件和航圖，並在航行過程中不停更新資料。 2019 年時，國泰航空進行首次無紙化飛行，節省重達 50 公斤的手冊、航圖、地圖和班機簡報文書工作。這項壯舉是透過一個高度客製化的 iPad 應用程式：Flight Folder。Flight Folder 是以MongoDB Atlas 建構而成，為的是改善飛航簡報體驗，MongoDB 協助將數十種資訊來源整合至一個平台，讓機組人員可以輕鬆與彼此分享體驗。應用程式中同時包含電子化加油功能，幫助機組人員在加油策略上更有效率，節省大量的飛行時間和成本。而 MongoDB Device Sync 功能則可進行無縫同步，就算應用程式在飛航過程中斷線也不會遺失資料。 自從發布 Flight Folder 之後，國泰航空駕駛艙內完全無紙化的班機已經超過 34 萬班次，除了大大改善機組人員的工作體驗之外，飛行時間也跟著減少，數位加油平均節省了 8 分鐘停留在地面的時間，同時也幫助公司減低了 1.5 頓的碳排放。 從批次走到即時 (From Batch to Real-Time) 阿達尼數位實驗室 (Adani Digital Labs) 基地位在印度的數位創新公司 阿達尼數位實驗室 ，是極具規模性的阿達尼集團的一部分。這間實驗室團隊宗旨在於建立一個單一的平台－稱為 AdaniOne 的超級應用程式，為印度眾多的故事發聲。 為了滿足不同的使用案例，加上這個超級應用程式的規模龐大，阿達尼數位團隊選擇MongoDB Atlas 作為主要的交易式資料庫，進一步增強 AdaniOne 的功能。 這個應用程式的重要任務是集中分散的資料，提供單一活動檢視頁面。在第一階段，開發者得以批次取出資料，再送進資料庫中。不過這麼做的速度太慢，而且就業務需求也無法預測狀況。除此之外，整合客戶歷史、訂單、庫存及供應鏈網絡的單一檢視畫面，可能會影響客戶的營收能力。 為了找到更好的解決方案，阿達尼數位實驗室建構與 MongoDB 相符、更現代的架構。有了MongoDB's Change Streams 和資料平台的原生 Kafka Connect，他們建構出事件導向的架構，取得可進行分析的即時資料。阿達尼數位實驗室的超級應用程式仍在草創的階段，而 MongoDB 的開發者平台可以繼續幫助公司成長並即時產出洞見。 產業 4.0 (Industry 4.0) 東華 (Dongwha) 東華集團 創立於 1948 年，已經由專注於木材產業，發展成為橫跨建築材料、化學品和媒體等多個領域的全球領頭公司。 東華的數位轉型計畫其中一部分是工廠智慧化，改善並提升生產效率。東華透過建立創新的智慧工廠軟體平台，搜集並分析資料，提升品質及生產管理能力。 最初，該平台是使用 MongoDB 的社區版本構建的。 不過為了擴大規模及提升應用程度，團隊近期遷移至雲中的 MongoDB Atlas。這一改變可以用最快的速度及最高的安全性儲存大量資料，優化時間序列資料的解決方案，並更容易運用資料進行機器學習。 東華的遷移過程非常順利，沒有發生任何工廠中斷或停機，目前已經應用在五間不同的工廠。在去年一整年，該應用程序的可用性和可靠性顯著提高，而且工廠業績已經成長六倍。 東華展望未來，計劃在國外的工廠應用這個平台。 數位原住民 (Digital Native) myBillBook 印度擁有 6000 萬間中小型企業，但其中只有非常小一部分進行電子化，大多數依舊用最原始的方式做生意。除此之外，許多印度企業目前也仍深受不穩定的網路服務、電力中斷及延遲所困擾。FloBiz 的任務就是與 myBillBook 一起改善這個狀態。 myBillBook 是一款一站式解決方案，幫助中小企業建立商業發票、管理股票、收取費用、透過智慧銀行進行自動化提示、與客人互動、管理人員出席及工資，還可以匯出超過 25 種不同的會計及決策商務報告。這款應用程式的設計是以行動裝置為導向，因此企業主只要透過手機和平板就能使用，而且不管是線上和線下的環境都能進行帳單和庫存管理。 myBillbook 是由 Mongo DB Atlas 技術支援，為企業提供靈活性及擴展性，可方便建立新功能及複雜的分析查詢。除此之外，資料平台中的行動資料庫 MongoDB Realm，支援線下使用及同步，確保不會因為網路訊號不好，造成資料遺失或是功能無法使用。這款應用程式成功支援客戶進行重要的商業營運，現在在印度有超過 6500 萬企業主使用 myBillbook 進行建立帳單、會計、收款以及促使業務成長。 客戶導向 (Customer Focused) 開泰商業科技集團 (KASIKORN Business-Technology Group) 開泰銀行(KBank)成立於 1945 年，是泰國規模最大且最古老的銀行之一。其任務為提供最佳服務，盡力滿足每一位客戶在生活和商務上的需求。開泰銀行其中一間子公司， 開泰商業科技集團(KBTG) 研發了一款行動金融應用程式，MAKE by KBank。MongoDB 的靈活性及方便開發的特性，讓 MAKE 研發部門可以依照任務選擇最適合的資料庫，也能使用 Atlas Online Archive 自動化進行資料分層，降低日常維護的工作時間，團隊因此有了更多時間專注在推出創新且獨特的功能，像是 Cloud Pocket，使用者可以無限客製化不同的資金用途，自己進行分配；另一個功能是 Pop Pay，使用者可以點擊位在附近的朋友大頭照，直接匯錢過去；另外是分析消費的功能 Expense Summary，幫助提醒及管理使用者的資金使用習慣。時至 2023 年 1 月，MAKE 已經擁有超過一百萬用戶，而過去一年，MAKE 上的交易數量已經從 90 萬筆成長至 750 萬。 大型規模 (Massive Scale) 中國移動 (China Mobile) 中國移動 透過其橫跨全國的行動通訊網絡，提供行動語音及多媒體服務，服務地區包含中國和香港。以總用戶數計算的話，是目前是全世界最大的行動網路業者。 這個行動通訊龍頭使用 MongoDB 支援其最大且最重要的推播服務，每個月向超過十億的用戶，寄送帳單明細。在應用 MongoDB 之前，技術團隊使用的是 Oracle 的服務，但用戶開始增加，服務性能卻開始走下坡。雖然投入了大量的資金，但是在像是完成及送出帳單這類的簡單請求，所需時間還是過長。在 2019 年時，中國移動進行全方面的測試之後，決定遷移至 MongoDB。MongoDB 的原生資料分片帶來的優勢，讓整體性能提升了 80%，而且同樣的工作量原本是由 50 台 Oracle 機器進行，現在降為 12 台。目前服務專注在當前需求上，並可以隨著未來增長進行擴展。 中國移動在 MongoDB 的支援下，穩定增加超過 1.68 億每月用戶，也成為中國移動集團中，擁有最高客戶滿意度的公司之一。
祝贺 2023 年度亚太地区创新奖获得者
我很激动能够在此公布 2023 年度 MongoDB 亚太地区创新奖的九位得主。MongoDB 创新奖褒奖志存远大的项目和人员。此奖项旨在表彰专业人员使用 MongoDB 构建引人注目的应用程序时对数据的突破性运用，以及突破技术限制时所发挥的创造力。今年我们设立了亚太地区奖项，表彰各行各业中从初创企业到行业龙头在内的所有组织在该地区所展现出的高远志向以及伟大成就。我们很荣幸能向大家推介以下获奖者： 2023 年度 MongoDB 亚太地区创新奖获得者： 积极影响 (Positive Impact) Open Government Products Open Government Products (OGP) 是一个由工程师、设计师和产品经理组成的内部团队，隶属于新加坡政府，负责构建可为公众谋福祉的技术。OGP 使用 MongoDB 的开发者数据平台 MongoDB Atlas 创建了自己的数字表单生成器 FormSG。新加坡政府和公共医疗机构使用 FormSG 安全收集居民和企业的相关数据，让公职人员能够在几分钟内创建政府数字表单。这样就无需再使用纸质表单，也不必再手动转录物理文档，消除了人们对数据隐私和保护的担忧。疫情期间，FormSG 协助公职人员在全国范围内收集超过 10 万份每日体温申报。如今，FormSG 已经为 155 家机构超过 12 万名公职人员提供服务，创建的数字表单超过 50 万份，帮助政府收集到访新加坡之游客的旅行和健康申报、新冠肺炎拭子检测申请以及财政援助申请的相关数据。 组织转型 (Organizational Transformation) Bendigo and Adelaide Bank Bendigo and Adelaide Bank 是澳大利亚规模较大的一家银行，旗下约 7,000 名员工，帮助超过 220 万个客户实现财务目标。多年来，该银行一直在推进转型，他们使用 MongoDB 的开发者数据平台提高效率、提供更出色的客户体验，实现了成为澳大利亚首选银行的愿景。 最近，云团队推出了 Ready-Set MongoDB (即 RSM)。这个事件驱动的框架支持开发人员简化内部或外部 API 的使用，且会在他们选择的 MongoDB 集合中自动应用数据转换和存储。这家银行还使用 MongoDB Atlas Search，让开发人员能够洞悉公司的多云部署，确定节约的成本额，并向帐户所有者和技术利益相关者提供清单信息。 这些计划启动不到 18 个月，自动化就已为组织省下 1,100 多天的开发工时。此举还有助于减少人工参与，删除了过时数据，使工程师能够专注于重要的事情。 Bendigo and Adelaide Bank 将面临新的多云挑战，MongoDB 新产品也会持续发布，因此，团队也将持续开发并不断改进 Ready-Set MongoDB。该应用程序完美地展示了本迪戈的技术部门如何利用现代技术、迅速开发以及以创新为导向的问题解决来推动组织转型。 医疗先驱者 (Heroes in Health) Redcliffe Lifetech Private Limited 在过去的几年内， Redcliffe Labs 已经成为印度发展最快的技术驱动诊断服务提供商。Redcliffe Labs 肩负使命，希望能够通过技术融合和世界级实验室，到 2030 年为 5 亿印度人提供服务。该公司已经在 180 个城市设立超过 73 个实验室和近 1,500 个免预约中心，每天为数千人提供服务。 Redcliffe Labs 依靠 MongoDB Atlas 的灵活文档模型为其创新的智能健康报告提供支持。作为一种患者资源，该报告提供的许多指标和跟踪器可用来衡量整体健康状况。MongoDB 开发者数据平台所具备的出色安全性、合规性和隐私控制让 Redcliffe 的团队能够自信地处理极为敏感的患者数据。 MongoDB Atlas 解决了许多传统的数据库管理挑战，这意味着开发人员可将事件用于为患者构建诊断服务，而不是管理数据库。Redcliffe Labs 目前的工作重点是利用 AI 平台将下一代技术融入诊断领域，从而创建交互式诊断报告、高级健康分析以及更详细的诊断和健康警报。 行业颠覆者 (Industry Disruptor) 国泰航空 (Cathay Pacific) 国泰航空 (Cathay Pacific) 是香港的本土航空公司，在全球 60 多个目的地国家/地区开展业务。其发展历程引人瞩目，成为了首批打造出真正无纸化驾驶舱的航空公司。直到最近，从香港飞往纽约的航班还需要机组人员先审阅 150 多页印刷精美的文本和图表后才能起飞，且整个飞行过程还需要不断更新各类文件。 2019 年，国泰航空进行了首次无纸化飞行，卸下的手册、图表、地图和飞行简报文件重达 50 千克。这个巨大成就有赖于一款无缝且高度定制的 iPad 应用程序 Flight Folder。基于 MongoDB Atlas 构建的 Flight Folder 旨在改善飞行员的简报体验。MongoDB 协助将数十个不同的信息源整合到一个位置，让机组人员能够轻松地与其他人分享他们的体验。这款应用程序还包括一个数字加油功能，可以帮助机组人员更高效地实施加油策略，从而节省大量的飞行时间和成本。使用 MongoDB Device Sync 可以实现无缝同步，不论飞行途中的应用程序是脱机还是联机，数据都不会丢失。 自 Flight Folder 推出以来，国泰航空已完成超过 34 万次飞行，驾驶舱实现了全数字化集成。除了大大改善了机组人员的体验外，飞行时间也相应减少，数字化加油平均节省了 8 分钟的地面时间。这些效率提升帮助公司避免了 1.5 万吨的碳排放。 从批处理到实时 (From Batch to Real-Time) 阿达尼数字实验室 (Adani Digital Labs) 阿达尼数字实验室 是阿达尼集团设于印度的数字创新团队。该实验室团队的一个重要任务是创建一个名为 AdaniOne 的超级应用程序平台，在印度为十亿个案例赋能。 为了应对该超级应用程序所需的诸多用例和巨大规模，阿达尼数字团队选择 MongoDB Atlas 作为其主要的事务数据库，而这将进一步增强该应用程序。 该应用程序的一个关键环节在于如何将不同的数据整合在一起，以便从单一平台查看应用程序上的全部活动。起初，开发人员批次提取数据并将其发送到他们的数据库。然而，就业务需求而言，此过程太慢，且不可预测。此外，将客户历史记录、订单、库存和供应链网络更新整合为综合性视图可能会影响其客户的创收能力。 因此，为了找到更有效的解决方案，阿达尼数字实验室借助 MongoDB 构建了更现代化的架构。使用 MongoDB 的变更流和数据平台的本机 Kafka 连接器，他们创建了一个基于事件的架构，可以实时推出数据并进行分析。阿达尼数字实验室仍处于超级应用程序推出的早期阶段，他们将继续将 MongoDB 作为其开发者数据平台，协助公司发展并实时提供见解。 工业 4.0 (Industry 4.0) Dongwha 成立于 1948 年的 Dongwha 集团 起初专注于木料和木材行业，现已发展成为横跨建筑材料、化学品和媒体等多个领域的全球领导者。 为了推进更广泛的数字化转型战略，Dongwha需要更智能的工厂来提高和优化生产效率。为此，Dongwha构建了创新型智能工厂软件平台，用于收集和分析数据，以提高质量和生产管理能力。 最初，该平台以MongoDB社区版本为构建基础。为了扩展规模和适应，该团队最近迁移到了 MongoDB Atlas。此举让他们能够以更快、更安全的方式存储大量数据，优化适用于时间序列数据的解决方案，以及轻松对数据执行机器学习。 Dongwha 无缝完成了迁移，工厂没有因此经历任何中断或停机。目前，已在五个不同的工厂推出了这款软件。在过去的一年内，该应用程序的可用性和可靠性显着提高，同时性能提高了 6 倍之多。未来，Dongwha 计划将该软件推广到旗下更多国际工厂。 数字原生 (Digital Native) myBillBook 印度拥有 6,000 多万个中小型企业 (SMB)，但只有一小部分中小型企业利用数字化，许多此类企业仍采用纸笔办公。此外，对于互联网服务的波动、中断和延迟，许多印度企业疲于应对。FloBiz 决意通过 myBillBook 来改变这一现状。作为一站式解决方案， myBillBook 可帮助中小型企业创建专业发票、管理库存、收款、通过智能银行自动发送提醒、与客户互动、管理员工考勤和工资单，还能够协助生成超过 25 份用于会计和决策的业务报告。此外，其还是一款移动优先程序，方便企业从移动设备访问。此外，其还允许用户在脱机和联机环境中管理帐单和库存。 myBillBook 应用程序由 MongoDB Atlas 提供支持，为企业提供了灵活和可扩展的基础，可以完成从构建新功能到执行复杂分析查询的所有工作。此外，数据平台中的移动数据库 MongoDB Realm 支持脱机使用和同步，可确保用户不会因互联网连线不佳而丢失数据或无法使用功能。鉴于 myBillBook 在支持客户开展业务关键运营方面的成功，印度有 650 多万企业主正在使用该应用程序进行计费、会计、收款并实现业务增长。 以客户为中心 (Customer Faced) KASIKORN Business-Technology Group 泰华农民银行 (KBank) 成立于 1945 年，是泰国规模最大、历史最悠久的其中一家银行。他们致力于努力追求卓越的服务，为每一位客户的生活和业务赋能。 KASIKORN Business-Technology Group (KBTG) 是泰华农民银行的一家子公司，其开发了一款移动银行应用程序 MAKE by KBank。MongoDB Atlas 的灵活性和开发简易性让 MAKE 的开发团队能够针对各任务选择最佳数据库，使用 Atlas 在线存档自动执行数据分层，缩短运行维护时间。将更多时间专注于为客户提供新的创新成果后，他们打造出 Cloud Pocket 等独特功能，可以将资金分配到数量不受限制的可定制 Pocket 中，可供单独使用。他们还推出了 Pop Pay 功能，支持用户轻松搜索附近的朋友，并通过点击个人资料图片实现转帐。此外，还提供支出分析服务“费用汇总”，有助于了解和管理用户的财务习惯。自 2023 年 1 月起，MAKE 收获的用户超过 100 万，并在一年的时间内将 MAKE 的事务数量从 90 万增加到超过 750 万。 超大规模 (Massive Scale) 中国移动 (China Mobile) 中国移动 ，在中国内地所有三十一个省、自治区、直辖市以及香港特别行政区提供全业务通信服务，业务主要涵盖移动话音和数据、有线宽带，以及其他通信信息服务。中国移动是全球网络和客户规模最大的世界级电信运营商。 中国移动使用 MongoDB 来支持其最大和最关键的推送服务之一，该服务每月向超过 10 亿用户发送账单明细。在使用 MongoDB 之前，中国移动技术团队一直依赖 Oracle数据库，但随着用户数量的增加，数据库性能也随之下降。尽管投入了大量资金，Oracle系统处理日常请求（如最终确定和向用户交付账单）仍然需要很长时间。 2019年，经过全面测试，中国移动迁移到MongoDB。通过利用 MongoDB 的原生分片，该系统性能大幅提高了80%，从原来需要50台Oracle机器减少至只需要12台MongoDB的机器来处理相同的负载。该推送服务不但可以处理所有当前需求，并为随着未来增长而扩展做好了准备。 借助MongoDB，中国移动推送服务业务稳步增长，月活用户超过1.68亿，该推送业务也成为中国移动集团里客户满意度最高的服务之一。
Introducing the MongoDB 5.1 Rapid Release
Arriving just a few months after the General Availability of 5.0, MongoDB 5.1 is our first Rapid Release which brings more native time series enhancements, richer analytics, new security options, and overall improvements to platform resilience and developer productivity. Launching alongside MongoDB 5.1 are new capabilities in Atlas Search which will make it easier for users to build fast and rich application search experiences. MongoDB 5.1 marks our accelerated release cadence designed to get new database features and improvements into your hands faster than ever before. MongoDB 5.1 and all future rapid releases will be fully supported on MongoDB Atlas and are available as development releases from our Download Center. Native Time Series Enhancements With optimized time series collections, clustered indexes, and window functions, MongoDB 5.0 made it faster, easier, and lower cost to serve the industry’s fastest growing, data intensive use cases such as IoT platforms and real-time financial analytics. Now with MongoDB 5.1, you can globally distribute your time series applications and further simplify their development: More developer velocity Time series collections can now take advantage of MongoDB’s native sharding to horizontally distribute massive data sets and co-locate nodes with data producers to support local write operations and to enforce the data sovereignty controls. It is common for time series data to be uneven, for example a sensor goes offline and several readings are missed. But in order to perform analytics and ensure correctness of results data needs to be continuous. With densification you can now handle missing data better and build time series apps and analytics faster putting less burden on the developer. Time series collections now also support delete operations . While most time series applications are append-only, users need to be able to invoke their right to erasure so we are giving developers an easy way to comply with modern data privacy regulations. Complete data lifecycle From medical sensors to market data fluctuations, time series means hundreds of millions data points per day. You need to process these massive volumes fast, distill valuable insights then continue to retain the full data set for regulatory purposes - possibly for years - all without incurring skyrocketing costs and data movement complexity. With Atlas Online Archive support for time series, now available in preview, you can do exactly that and seamlessly and economically manage your entire time series data lifecycle. Simply define your own archiving policy, and Atlas handles all data movement for you by tiering aged time series data out of your database into lower cost, fully managed cloud object storage. Rather than delete anything, you can retain all your time series data, preserving the ability to query it at any time alongside your live data for long term trend analytics and machine learning, or for compliance purposes. Support for online archiving is available for MongoDB 5.0 and above. Broader platform support for Time Series Data Our native time series capabilities are supported across the entire MongoDB data platform making it easy to work with time series data in any context. You can now create time series collections directly from Atlas Data Explorer, MongoDB Compass or MongoDB for VS Code. With support for date binning, date filtering options, and value comparison, Atlas Charts lets you create graphs and dashboards from any Atlas times series collection, easily share insights, and embed visualizations into your applications for a rich user experience. Richer and More Flexible Analytics and Full-Text Search Many developers start out with MongoDB for their operational use cases, and then expand to leverage our platform's versatility in powering analytics and search as well. MongoDB 5.1 includes new features and enhancements that make it easier to unlock insights from your data and improve user experience. Cross-shard joins and graph traversals For most transactional and operational workloads, the document data model largely eliminates the need to join data from different collections. This is because related data can be embedded in sub-documents and arrays within a single, richly structured document – following the principle that what is accessed together is often best stored together. However analytical applications can sometimes require joins to be executed – for example bringing together customers and orders from separate collections. Through the $lookup aggregation pipeline stage, you can have the database join collections for you. The $graphLookup stage gives you the ability to traverse related data, performing “friend-of-friend” type queries to uncover patterns and surface previously unidentified connections in your data. In MongoDB 5.1 we now allow you to use $lookup and $graphLookup to combine and analyze data that is distributed across shards which was not previously possible. Our design gives you even more precision in your code by enabling you to target individual shards as needed. However you don’t need to understand sharding or even know your collection is sharded to run these queries as there is no new syntax for developers to learn. Materializing results for operational analytics The $merge and $out aggregation stages can be used to write the results of an aggregation pipeline in order to create a new collection or create/update an on-demand materialized view . These stages enable users to reduce processing overhead by reading pre-computed results instead of re-running the aggregation each time, and by writing only incremental results when the aggregation results change. Users often want to run resource-intensive analytical queries on secondary nodes in order to avoid performance impacts on the primary — but since only primaries can serve writes, aggregations including $out or $merge could not previously run on a secondary node. Soon, such pipelines will run, performing their query execution work on a secondary node, then automatically directing any writes to the primary. This allows you to offload computationally expensive analytics work to secondary nodes while still being able to materialize the results of that work. This will be accessible via drivers in their upcoming releases. Full-Text Search Facets: now in public preview Faceted search allows users to filter and quickly navigate search results by categories and see the total number of results per category for at-a-glance statistics. With our new facet operator , facet and count operations are pushed down into Atlas Search’s embedded Lucene index and processed locally, taking advantage of 20+ years of Lucene optimizations. This makes workloads such as ecommerce product catalogs, content libraries, and counts run up to 100x faster . Learn more from our Atlas Search facets blog post . New and Enhanced Security Options End-to-end encryption for confidential computing Extending beyond cloud provider Key Management Services (KMS), MongoDB’s unique Client-Side Field Level Encryption will support any KMIP-compliant KMS . This functionality is being released in new versions of drivers that will be available soon. Client-Side FLE delivers some of the strongest privacy and security controls available anywhere today. By using the MongoDB drivers to encrypt the most sensitive fields in your documents before they leave the application you can do three things that are not possible with in-flight or at-rest encryption alone: Protect data while it is in-use, in the memory of your active database instance. The database never sees plaintext, but data remains queryable. Make data unreadable to anyone running the database for you, or who has access to the underlying database infrastructure — this includes MongoDB SREs running the Atlas services as well as cloud provider personnel. Simplify the process of enforcing right to erasure (sometimes called right to be forgotten) mandates in modern privacy regulations such as the GDPR or the CCPA. This is because you simply destroy the key encrypting a user’s PII, and their data is rendered unreadable and unrecoverable — in-memory, at-rest, in backups, and in logs. Google Cloud Private Service Connect We’ve also added a new network security option to MongoDB Atlas with the availability of Google Private Service Connect (PSC). Private Service Connect allows you to create private and secure connections from your Google Cloud networks to MongoDB Atlas. It creates service endpoints in your VPCs that provide private connectivity and policy enforcement, allowing you to easily control network security in one place. Along with VPC Peering, Google Cloud PSC makes it easy to connect your applications and services in Google Cloud to Atlas. Platform Resilience MongoDB 5.1 continues to build out controls for reliability and availability with the following enhancements: We've made a number of changes to WiredTiger internals that improve backups, including minimizing the checkpoints pinned while a backup cursor is open and improving handling of backup cursors that are open for long periods. These improvements will reduce both the operational overhead and storage consumption on the replica node from which the backup is taken. This improvement is available for backups taken from MongoDB Atlas and from self-hosted deployments controlled by Ops Manager or Cloud Manager, and has been backported to MongoDB 4.2 and above. In addition to enhancements affecting backups, WiredTiger checkpointing and locking have been improved to enhance performance when MongoDB is managing many concurrently active collections in a single instance. This is especially useful to multi-tenant applications built on MongoDB. We'll also be adding improvements in upcoming versions of our drivers that support mongos controls to mitigate connection storms in sharded clusters, especially during failover events. These include preferentially connecting to nodes that have existing idle connections that can be reused, improving the matching of connection pool sizing across replica set members, limiting the rate of new connections, and adding a mechanism to limit the number of mongos servers used when connecting to sharded clusters via SRV records. Improved Productivity for C# Developers Making it easier for developers to query and manipulate data is at the core of our mission. For C# developers the LINQ API serves as the main gateway between the language and database. In MongoDB 5.1 we are improving developer productivity for our C# community with a completely redesigned LINQ interface that lets developers write all of their MongoDB queries as well as build sophisticated aggregation pipelines natively in C#. Getting Started with MongoDB 5.1 You can learn more about all of the new features and enhancements in MongoDB 5.0 and 5.1 from our Guide to What’s New . MongoDB 5.1 is available now. If you are running Atlas Serverless instances or have opted in to receive Rapid Releases in your dedicated Atlas cluster, then your deployment will be automatically updated to 5.1 starting today. For a short period after upgrade, the Feature Compatibility Version (FCV) will be set to 5.0; certain 5.1 features will not be available until we increment the FCV. MongoDB 5.1 is also available as a Development Release for evaluation purposes only from the MongoDB Download Center. Consistent with our new release cadence announced last year, the functionality available in 5.1 and the subsequent Rapid Releases will all roll up into MongoDB 6.0, our next Major Release scheduled for delivery in 2022. I really look forward to hearing what you think about MongoDB 5.1, and can’t wait to tell you what’s new in the 5.2 Rapid Release scheduled for next quarter. Safe Harbour Statement The development, release, and timing of any features or functionality described for our products remains at our sole discretion. This information is merely intended to outline our general product direction and it should not be relied on in making a purchasing decision nor is this a commitment, promise or legal obligation to deliver any material, code, or functionality.
Re-Imagining What A Cloud-Native Database Can Be
COVID-19 has compelled companies of all sizes and industries to reinvent themselves. From the way they work to the way they interact with customers, the pandemic has forced an urgent shift to a digital-by-default customer experience and, as a result, has accelerated the move to the cloud. But as companies make the move, many are finding that the same data silos and operational complexity that thwarted innovation for decades is simply following them into the cloud. Developers responsible for building today’s apps have to work with a patchwork of technologies, data models, APIs, and languages across disparate systems to deliver the right data at the right time to power critical applications and services. To better serve these developers, we’ve expanded our capabilities outside of the core database into a robust data platform we call MongoDB Cloud . At its core is MongoDB Atlas, our fully managed global cloud database, which enables your developer teams to spend less time on undifferentiated work and more time writing code that adds business value. By adding capabilities such as Atlas Search , Atlas Data Lake , MongoDB Charts and MongoDB Realm , which provide a consistent experience for working with data in different ways, you’re drastically reducing the cognitive burden on development teams. Simply put, MongoDB Cloud allows you to easily deploy, manage, and scale data architectures designed to support the converging requirements of transactional and analytical systems within a single elegant platform. Any cloud, anywhere, anytime The pandemic has put a spotlight on resilience and agility and showcased the importance a data platform can have for your business. This has not only accelerated the migration to the public cloud, but also the move to multi-cloud environments. Many of our customers rely on more than one cloud provider, and 55 percent of organizations currently report using multiple public clouds . That’s why we designed our offerings to have the same great developer experience regardless of which cloud provider or providers you use. Since launching in 2016, MongoDB Atlas has always pushed the boundaries of what’s possible in cloud data management, with customers able to deploy their data from more than 75 regions worldwide across AWS, Azure, and Google Cloud. And with the recent launch of multi-cloud clusters on MongoDB Atlas, we’ve recast the cloud and development experience again. With this first-of-a-kind capability, companies gain the ability to distribute their data in a single cluster across multiple public clouds simultaneously, or move workloads seamlessly between them. This is true data portability, enabling the freedom and flexibility to use best-of-breed services across multiple platforms, and ensuring cross-cloud resiliency. But we’re not standing still. Introducing Online Archive on MongoDB Atlas Today, we are announcing more innovations that unleash the full potential of business data, beginning with the general availability (GA) of Online Archive for MongoDB Atlas. With Online Archive, you can seamlessly tier your data across fully managed databases and cloud object storage, all while retaining the ability to query it through a single endpoint. Users can create a rule to automatically archive infrequently accessed data in their MongoDB Atlas clusters onto their object store, eliminating operational complexity and transactional data storage costs. All users on dedicated clusters (M10+) can use Online Archive regardless of which cloud provider they are using to run Atlas. If you want to learn more or see if Online Archive could help your organization, watch our deep-dive technical session , which is available on demand and features a live Q&A on Wednesday, Dec. 2 from 3:30-4pm ET. Online Archive gives me the flexibility to store all of my data without inucrring high costs, and feel safe that I won't lose it all. It's the perfect solution. Ran Landau, CTO, Splitit The power of choice Empowered developer teams around the world turn to MongoDB Atlas on their preferred cloud to deliver mission-critical services to their businesses faster. Here are a few customer success stories that are near and dear to our hearts: Ludo King : The small but mighty team of developers behind India’s favorite mobile game, Ludo King, turned to MongoDB Atlas and MongoDB Realm on AWS. The results? They’ve been able to keep building new, revenue-generating features for the game’s half a billion players, while efficiently managing near instantaneous 1000% growth. Toyota Materials Handling Europe : While building the connected warehouses of the future, Toyota Material Handling needed a database as flexible and powerful as MongoDB Atlas, running on Azure, to break down their monolith and transition to a microservices architecture. Boxed : Grocery delivery wholesaler Boxed built its platform on MongoDB Atlas on Google Cloud to accommodate the soaring demand for goods and services due to the pandemic. As brick-and-mortar retailers struggled to keep up with demand, Boxed saw a 30x spike in demand, which they were able to handle because of MongoDB’s powerful data platform. Get started with MongoDB Atlas today. And make sure you take advantage of all the opportunities to explore MongoDB at AWS re:Invent 2020 .
Introducing Multi-Cloud Clusters on MongoDB Atlas
One of the core pillars of MongoDB is the freedom to run anywhere. Since 2017, organizations have been able to use MongoDB Atlas , our fully managed global cloud database, across 70+ regions on the cloud provider of their choice: AWS, Azure, or Google Cloud. We’re increasingly seeing customers run independent workloads on different clouds — a common practice among enterprises with different applications and business units. However, we believe the real power of multi-cloud applications is yet to be realized in our industry. So today, I’m proud to announce that multi-cloud clusters are generally available on MongoDB Atlas! With this groundbreaking capability, customers can distribute their data in a single cluster across multiple public clouds simultaneously, or move workloads seamlessly between them. Data — traditionally the hardest piece of an application stack to move — is now the easiest. A New Multi-Cloud Paradigm More organizations are moving towards a multi-cloud model , and they want the freedom and flexibility to use the best of each cloud provider for any and every application. The question is how engineering teams can do this efficiently and deliberately while dealing with challenges such as incompatible operations and the effects of data gravity . Read our eBook, Why the World is Going Multi-Cloud , for a high-level guide to today's fast-emerging cloud architecture. Download Now With multi-cloud clusters on MongoDB Atlas, customers can realize the benefits of a multi-cloud strategy with true data portability and a simplified management experience. Developers no longer have to deal with manual data replication, and businesses can focus their technical resources on building differentiated software. This opens up a whole new set of possibilities that were previously difficult ― if not impossible ― to achieve, from being able to use best-of-breed services across multiple platforms to data mobility and cross-cloud resiliency. Use best-in-class technology across multiple clouds in parallel Developer productivity is critical to a company’s success, and CTOs know that enabling their teams to choose the best technology available is a major contributing factor. With MongoDB Atlas, developers get more freedom in deciding what building blocks to use, regardless of which cloud is storing application data. Some examples of popular cloud services that our customers like to use include AWS Lambda , Google Cloud AI Platform , and Azure Cognitive Services. With multi-cloud clusters, developers can now run operational and analytical workloads using different cloud tools on the same dataset, with no manual data replication required. Migrate workloads across cloud environments seamlessly Data mobility is another reason companies want a multi-cloud strategy. The world is constantly changing, and businesses never know if, or how, their cloud requirements are going to change. They may face mergers and acquisitions, be subject to new regulatory controls for data portability, find themselves in direct competition with a cloud provider, or find significant cost savings on another platform. With MongoDB Atlas, organizations can future-proof their applications and have the option to move them from one cloud to another if needed, without undergoing a costly data migration. Our built-in automation seamlessly handles cross-cloud data replication on a rolling basis so applications stay online and available to end-users. Improve high availability with cross-cloud redundancy Any business with a mission-critical or user-facing application knows that downtime is unacceptable. Cloud disruptions vary in severity, from temporary capacity constraints to full-blown outages, and organizations need to mitigate as much risk as possible. By distributing data across multiple clouds, they can improve high availability and application resiliency without sacrificing latency. MongoDB Atlas extends the number of locations available by allowing users to choose from any of the nearly 80 regions available (with more coming) across AWS, Azure, and Google Cloud — the widest selection of any cloud database on the market. This is particularly relevant for businesses that must comply with data sovereignty requirements , but have limited deployment options due to sparse regional coverage on their primary cloud provider. In some cases, only one in-country region is available, leaving users especially vulnerable to disruptions in cloud service. For example, AWS and Google Cloud each offer only one region in Canada. With multi-cloud clusters, organizations can take advantage of both regions, and add additional nodes in the Azure Toronto and Quebec City regions for extra fault tolerance. With MongoDB Atlas, customers no longer need to make a trade-off between availability and compliance. Reach more users with flexible deployment options In order to deliver a world-class application experience, organizations must at a minimum meet end-user requirements for their products and services. For SaaS providers and B2C businesses, this may include cloud provider preferences or regional availability. While each of the cloud providers offer a large and growing list of regions globally, their data centers are still heavily concentrated in the USA, Europe, and eastern Asia. If multinational enterprises want to reach local users in other areas, they may not always find coverage on a single cloud. For example, AWS is the only provider to offer a cloud region in Bahrain, Azure Oslo is the only option in Norway, and only Google Cloud has data centers in Indonesia. To capture more global market share, companies may need a multi-cloud strategy to meet customers where they are. An Integrated, More Secure Cloud Data Platform MongoDB has consistently delivered innovations in the data management experience, including automated data tiering with Atlas Online Archive , integrated full-text search with Atlas Search , and Client-Side Field Level Encryption (FLE) for some of the strongest levels of data privacy available today. Client-Side FLE currently works with AWS Key Management Service (KMS), and will soon offer beta support for Azure Key Vault and Google Cloud KMS. With this expansion, it will be easier for organizations to further enhance the privacy and security of sensitive and regulated workloads across all major public cloud platforms. Read our guide to learn more about how Client-Side Field Level Encryption protects data in MongoDB. Download Now Multi-Cloud Data Management Made Easy Multi-cloud distribution can be enabled for both new and existing clusters starting today via the Atlas UI. Multi-cloud clusters come with all the features that our customers know and love, including built-in security defaults , fully managed backup and restores , automated patches and upgrades , intelligent performance advice , and more. While multi-cloud clusters are generally available, we are planning on releasing more capabilities in the coming months to deliver even more value to you. Whether you’re a startup just getting off the ground or a global enterprise in the midst of a multi-year cloud transformation initiative, our multi-cloud database solution abstracts away the toughest roadblock to unlocking your multi-cloud strategy. When your data can travel across clouds, there’s no limit to what you can build. Let us know where multi-cloud clusters on MongoDB Atlas take you - or tell us what you need to get there .
Announcing MongoDB 4.4 and MongoDB Cloud
Today at MongoDB.live, we’re announcing a number of new products and services that expand what you can do with MongoDB. Join the event (free and entirely virtual) to learn more, or read about the news on our announcements page . At MongoDB, our mission is to free the genius within everyone by making data stunningly easy to work with. For many years, that’s meant building a database with an intuitive and flexible document model, plus a distributed systems architecture for resilience and horizontal scale-out. Of course, the modern data architecture isn’t limited to only the transactional database. Many applications also require analytics and search functionality, which often requires teams to learn, deploy, and manage additional systems. If you’re building mobile apps, you’ll need to deal with data on the device and syncing it to the backend. You may also find yourself building data visualizations, writing a lot of glue code to move data between data services, or creating and operating custom data access APIs. We want to make all of that easier. Today, alongside a new version of MongoDB and improvements to MongoDB Atlas, we’re announcing new products that go beyond the database and deliver a consistent experience for developers, wherever data resides. These are all part of MongoDB Cloud , a unified data platform for modern applications. MongoDB 4.4 MongoDB 4.4 , the latest version of the database, is now available in preview; you can try it out in MongoDB Atlas or download the development release. We think of MongoDB 4.4 as “user-driven engineering”, delivering a number of the features and improvements that have been most requested by the MongoDB community. Headline features of MongoDB 4.4 include: Aggregation enhancements: use the new Union stage to combine data from multiple collections into a single result set, define your own Custom Aggregation Expressions, and use new operators for array handling, string manipulation, and more. Refinable shard keys: as you scale, modify data distribution by adding suffixes to your shard key. Hedged reads: submit read requests to multiple replicas returning results from the fastest node. Mirrored reads: mirror a configurable subset of reads to secondaries, keeping their caches warm . The latest release also includes other features such as compound hashed shard keys, resumable initial sync, streaming replication, global read and write concerns, and more. To learn more about what’s coming, read our guide to what’s new in MongoDB 4.4 . MongoDB Cloud The best way to use MongoDB is with MongoDB Atlas , our fully-managed global cloud database. Atlas now makes it even easier to manage and optimize MongoDB with new functionality that allows you to run the database on auto-pilot: Atlas Auto-Scale , previously preview, is now Generally Available: Atlas monitors metrics in real time and adjusts cluster compute and storage to meet the needs of your workload. Atlas will now proactively give you advice on how to model your data for the best performance. Schema suggestions , available in both the Atlas Performance Advisor and Data Explorer , use database metadata and logs to flag common anti-patterns when working with the document data model. This includes having documents that are too large, having too many collections or indexes, using unbounded arrays, and more. Atlas is the core of MongoDB Cloud, a unified data platform for modern applications. MongoDB Cloud provides a data foundation, unifying different data services with a common developer experience from cloud to edge. We’re excited to launch many of these data services today. Atlas Search , now GA, is built into Atlas. Instead of deploying a separate search technology and coordinating data synchronization with your transactional database, you can create search indexes right in Atlas and access them with the same MongoDB aggregation framework you’re already familiar with. Atlas Data Lake , also generally available today, helps realize the value of your data lake faster by querying data in any format on Amazon S3 using the MongoDB Query Language (MQL). You can query your existing S3 data or even enable automated tiering of data between the Atlas Cloud Database and Data Lake. Atlas Online Archive , available today in preview, automatically moves older data into Data Lake while preserving query access across both tiers with federated queries. This data foundation reaches to the edge with the Realm Mobile Database , compatible with both iOS and Android. Mobile apps need local access to data, and Realm makes it happen without taking up too much space or draining your battery. Realm Sync , available in preview, automates the process of syncing bi-directionally with a backend Atlas cluster, with built-in conflict resolution. Beyond the data foundation, MongoDB Cloud offers application services that simplify building apps with MongoDB. MongoDB Realm’s application development services include serverless functions, which execute application logic based on real-time database changes or on a schedule, and a GraphQL Service that makes it easy to expose a GraphQL API for MongoDB Atlas. MongoDB Charts is the best way to build visualizations of MongoDB data and now makes accessing and sharing those visualizations even easier, whether directly or a part of an application. The new embedding SDK makes it easier to build charts into your applications and control them directly from application code. Dashboard filtering lets users define a data filter to be applied across all charts on a dashboard, customizing it according to their needs; each user of a shared dashboard can have a different, personalized filter. Dashboards can now also optionally be shared with a public link, giving view-only access to unauthenticated users. Tools and Integrations We’ve also announced a number of tools and integrations that make working with the database easier. A new MongoDB shell is now available in preview, and improves on the existing shell with autocomplete, syntax highlighting, contextual help messages, and more. You can also work with MongoDB in your IDE of choice with new integrations for VS Code and Jetbrains products. A new CLI for MongoDB Cloud adds an easily scriptable way of provisioning and controlling cloud resources. Alongside the UI and the API, you can now manage your cloud environments from your command line. If you’re managing MongoDB yourself, two new Kubernetes announcements make the process easier. If you’re an Enterprise customer using our Enterprise Kubernetes Operator with Ops Manager, you’re now able to run Ops Manager itself in Kubernetes , simplifying the setup process. If you’re using the community version of MongoDB, a new MongoDB Community Kubernetes Operator enables you to deploy simple containerized MongoDB clusters. Two new GA drivers expand our language support . The Rust driver , previously available in alpha, is now generally available, supporting this fast-growing language. Expanding the mobile development capabilities we bring with MongoDB Realm, we’re also announcing a new driver for Swift . Get Building in the Cloud We’re very excited about everything we’ve announced today. If you are too, you can get started with some of the new functionality by creating a free MongoDB Atlas account in minutes. We can't wait to see what you build! Safe Harbor Statement The development, release, and timing of any features or functionality described for MongoDB products remains at MongoDB's sole discretion. This information is merely intended to outline our general product direction and it should not be relied on in making a purchasing decision nor is this a commitment, promise or legal obligation to deliver any material, code, or functionality. Except as required by law, we undertake no obligation to update any forward-looking statements to reflect events or circumstances after the date of such statements.
New to MongoDB Atlas: Performance Advisor, Auto-Expand Storage Capacity, Teams
MongoDB Atlas includes a set of monitoring capabilities that give your teams complete visibility into the performance of your databases, allowing you to anticipate issues and proactively take the necessary steps to ensure an optimal experience for your end customers. Important historical metrics are automatically highlighted in optimized dashboards. It’s easy to create and customize alerts that ping the endpoints you want when key metrics go out of range. You can also see what’s happening in your cluster as it happens with the real-time performance panel, which displays memory usage, network I/O, operations in flight, the hottest collections, and the slowest operations. This panel even allows you to kill slow-running operations with just a few clicks. Real-time performance panel Automated index suggestions with the new Performance Advisor But what if instead of killing off those operations, you wanted a quick and easy way to see how to improve their runtime? That’s now easy with the new Performance Advisor, available for all dedicated MongoDB Atlas deployments. The Performance Advisor shows the different collections in your database that are experiencing suboptimal performance. Click on a specific collection and it will display existing indexes, examples of slow-running queries and relevant metrics, and most importantly, automatically generated index suggestions to help improve their performance. New Performance Advisor, available for all dedicated MongoDB Atlas deployments This new feature runs in the background with no impact to your existing deployments and ensures that you’re getting the most performance out of MongoDB with the resources you’ve provisioned. Automatically expanding storage capacity When you do need additional resources, MongoDB Atlas now makes that process easier to manage with automatic scaling for storage capacity. Enabled by default for all dedicated clusters (M10 instance size and above), auto-scaling for storage detects when your disks hit 90% utilization and provisions additional storage such that your cluster reaches a disk utilization of 70% on AWS & GCP, or a maximum of 70% utilization on Azure. This automated process occurs without impact to your database or application availability. Simplified user management with Teams MongoDB Atlas makes it easy to manage your database footprint with a simple hierarchy optimized for organizations made up of multiple business units. Projects contain MongoDB clusters; clusters in a project do not necessarily have to be in the same region. Organizations are made up of different projects that share the same billing settings. And today, we’re introducing teams , which will help simplify database user management. All users in a team will share the same access to a project . Teams can have access to multiple projects and users can belong to multiple teams . Changelog New disk size options for customers running on Microsoft Azure. 32GB, 64GB, 256GB, 512GB, 2TB, and 4TB disk sizes are now available. Free tier is now also available in AWS Frankfurt (EU-Central-1) Have feedback about a new feature or MongoDB Atlas? As always, we’d love to hear it at email@example.com . Not an Atlas user yet? Get started with a 512MB database for free.
New to MongoDB Atlas: More Azure Regions, Monitoring Metrics via the API, Cross-Project Restores, Test Failover
Earlier this year, we announced the availability of our cloud database service, MongoDB Atlas, with global support for Amazon Web Services, Microsoft Azure and Google Cloud Platform. And since then, we’ve been humbled by the overwhelming reception from the global community of MongoDB users. Customers like Ticketek — Australia’s largest ticketing company in sports and entertainment — which now uses MongoDB Atlas to support the core transactional systems needed to power their multi-channel ticket sales and distribution network. “Everyone knows Ticketek from an A/NZ perspective, but we’re also delivering tickets in the US and UK and we recently bought the largest ticketing company in Malaysia,” explained Matt Cudworth, CTO of TEG, Ticketek’s parent company, in an interview with itnews.com.au . “Atlas became an obvious choice for us to be able to deliver [services] in most regions. We can use different cloud providers, and you can’t go past [a managed service by] the vendor that makes the software. There’s no better expert in that technology.” More Atlas Regions on Microsoft Azure Today, we’re excited to announce that MongoDB Atlas now supports 23 Azure regions across the world. This will grant the increasing number of MongoDB users looking for a cloud database service global low latency connectivity and the ability to meet data sovereignty requirements. New MongoDB Atlas regions on Microsoft Azure You can now deploy clusters with MongoDB Atlas in 41 regions across AWS, Azure, and GCP. Log in to your account to see the full region list. New MongoDB Atlas Features We’ve also been working on adding features based on user feedback. Here are just a few quick highlights: Support for monitoring metrics and logs via Atlas API You can now obtain fine-grained monitoring metrics on database processes and the underlying instances via the MongoDB Atlas API . In addition, the API will allow you to retrieve log files for a particular host. Cross-project restores You can now perform backup restores into a different Project (formerly Group) than the backup snapshot source. This allows you to easily execute tasks such as creating multiple staging or test environments that match recent production data with different user access privileges or in different regions. Test failover / “Chaos” button Modern cloud applications should be designed for high availability despite instance failures. With the new “Test Failover” button — available for all dedicated clusters — MongoDB Atlas will trigger a replica set failover and subsequent election, helping you test redundancy and ensure that your application connection handling is resilient. All of these new features are now live in MongoDB Atlas. As always, we’d love to hear your feedback at firstname.lastname@example.org . Not an Atlas user yet? Get started with a 512MB database for free.