Announcing MongoDB's Giant of the Month, Doug Duncan of Alteryx
January 27, 2016
MongoDB customers and community members are the people who realize GIANT ideas. We are excited to begin highlighting some of our community members, our MongoDB Giants, who are tackling challenging problems and bringing solutions to life with MongoDB.
This month’s MongoDB Giant is Doug Duncan, a DBA at Alteryx, who is making a meaningful impact to the MongoDB community. Alteryx is a leader in data preparation, blending, and advanced analytics.
Doug has worked with RDBMSs for longer than he cares to admit, focusing in both development and administration. Through his experience, Doug grew to embrace new data storage technologies. He began working with MongoDB several years ago (starting with the MongoDB 1.8 release in early 2011) both professionally and recreationally. Doug acted as an online TA the first two years following MongoDB University’s founding, working closely with the team by answering students’ questions about the M101J, M101JS and M202 courses, as well as providing questions used in the courses. For his contributions to the education team Doug was awarded the first ever MongoDB DBA certification back in November of 2013.
Doug also periodically answers questions on the MongoDB Google group. This year he will increase his participation in the community by delivering talks at the Denver MongoDB User Group.
In his spare time, if Doug’s not reading up on MongoDB, Hadoop, or other distributed data stores, you can find him walking around the foothills of Colorado with his wife, two boys and two dogs.
Become an important part of the MongoDB community. Join our Advocacy Hub and start getting involved today.
Leaf in the Wild: SilkRoute Chooses MongoDB Over SQL Server for Critical Quality Assurance Platform
Leaf in the Wild posts highlight real world MongoDB deployments. Read other stories about how companies are using MongoDB for their mission-critical projects. MongoDB chosen for development productivity, operational efficiency with Cloud Manager, and “truly outstanding” professional services From manufacturing to retail, every part of the supply chain is starting to see the value of data. Whether it’s developing IoT quality assurance applications in manufacturing to ensure your products are defect-free or building data-driven customer loyalty programs so that brands can connect with and reward their fans, the top companies are working to improve their approach to data. SilkRoute Global is a software-as-a-service company focused on this industry. Its analytics products automate processes and present consumable, useful information to its customers. To understand the benefits they get from MongoDB, I spoke with Devin Duden, CTO of OmniSky (a division of SilkRoute) & Senior Software Engineer, and Amjad Hussain, CEO & Chief Data Scientist. Tell us a little bit about SilkRoute. SilkRoute is a passionate team of designers, machine learning scientists, and software engineers with tremendous industry knowledge of manufacturing, distribution, and retail. We live for solving big problems. Our industry-specific predictive and prescriptive analytics platform creates immense operational and strategic value for our customers. Our customer footprint is global and growing. Applied machine learning, business process automation, and mobility are woven into the fabric of everything we build. We offer a unique risk-free rapid implementation and integration approach for our customers to enjoy our solutions. Please describe how you’re using MongoDB. The application SilkRoute is building is a mobile application performing RFID inspections on industrial manufactured products. The application provides a centralized data store of customers’ products and the inspections associated with a product, and allows those customers to easily share the inspection records with others. MongoDB was chosen for this application based on: Simplified schema design Increased flexibility for modeling complex relationships (e.g., using MongoDB eliminated recursive relationships necessary in a SQL-based solution) Easier capture of user generated data Reduced development timeline Durability, scalability, and disaster recovery SilkRoute Enterprise mobile RFID inspection architecture What were you using before MongoDB? Was this a new project or did you migrate from a different database? The current version of the application is a client-server implementation using SQL Server as a cloud sharing data store and Windows CE on the mobile device. The application is a rewrite. How did you hear about MongoDB? Did you consider other alternatives, like relational or NoSQL databases? I was introduced to MongoDB three years ago when I started working at SilkRoute. We were working on a social network at the time, which was using MongoDB as its primary data store. The RFID mobile application’s technical requirements were originally to use MS SQL Server. This technical requirement was provided by the client. During our working Joint Application Design session with the client, we suggested using MongoDB, but didn’t make headway. When we attended MongoDB World 2015 , we gathered enough details about MongoDB’s capabilities, along with real-world examples of high-volume, transaction-based applications being developed on MongoDB, that we were able to persuade the client to switch from SQL Server to MongoDB. Please describe your MongoDB deployment, technology stack, and the version of MongoDB that you are running. The MongoDB deployment is a 5 node replica set using Cloud Manager for operational management and deployment. The replica set is deployed in the US East AWS region across all availability zones. At this point, we have not implemented sharding. The MongoDB replica set has been deployed in AWS following MongoDB’s best practices using Amazon Linux AMIs. Each production node will be running on EC2 instances with 16 GB memory and 4 core CPUs, with three 100GB provisioned IOPS EBS volumes. Each volume is XFS format. One volume is mapped for “data”, one volume is mapped for “log”, and one volume is mapped for “journal”. The API stack is written in .NET 5 using C# MVC/Web API framework. We are using the MongoDB .NET driver version 2.0. Are you using any tools to monitor, manage and backup your MongoDB deployment? If so what? Do you use Ops Manager / Cloud Manager? The replica set has been deployed and managed using Cloud Manager. Cloud Manager simplified and streamlined replica set deployment and operations. This solution is the first time the majority of team members used MongoDB. To reduce time spent with MongoDB replica set deployment and configuration, Cloud Manager was a great fit. Following Cloud Manager’s directions to create AWS EC2 instances made it very easy for us to create images, and build/tear down replica sets quickly. Streamlining manual tasks allowed the team to focus more time on development than deploying a fully managed MongoDB replica set. In addition to Cloud Manager, the team just started using MongoDB Compass to analyze collections and document sizes. Are you integrating MongoDB with other data analytics, BI or visualization tools? If so, can you share any details? At this point we have not integrated any BI. One of our objectives is to connect with the client’s BI system using the MongoDB Connector for BI and/or extract data from a tagged node to hydrate a SQL-based BI system. We’re planning to perform a POC on the Connector for BI, now that it has been released. How are you measuring the impact of MongoDB on your business? SilkRoute measures MongoDB’s impact by many factors, including ease of use with deployments, a code first approach, increased agile development model, reduced total cost of ownership, and reduced time to market. The ease of deployments reduces or eliminates maintenance windows when spinning up a replica set or upgrading database versions, which means higher uptime for customers and less productive time eaten up for developers. A code first approach adds to increased savings by eliminating daunting DDL script management and aids with better agile development. These factors result in reduced total cost of ownership and faster time to market. Do you use any commercial subscriptions or services to support your MongoDB deployment? SilkRoute is a MongoDB OEM partner. For the RFID application we will be embedding MongoDB Enterprise Server 3.2 and managing the deployment with Cloud Manager. We allocated a budget for MongoDB’s professional services in the early stages of the project. The professional services were tailored to the team’s skill set and agenda. With two separate onsite sessions, we covered topics from deployment, management, and recovery using Cloud Manager, to schema modeling and scaling. The value gained working hands-on directly with a MongoDB consulting engineer was twice the investment. During one session, we encountered a disaster recovery situation in a non-production environment. Unexpected though the situation was, I personally gained the most from the experience of working through the issue with a MongoDB expert in a very collaborative fashion. The professionalism and knowledge of our MongoDB consulting engineer was truly outstanding. Do you have plans to use MongoDB for other applications? If so, which ones? Yes, both internal initiatives and client initiatives. These include BI, a Warehouse Manager SaaS solution, a customer loyalty/couponing app, and client SaaS solutions, which we are not at liberty to disclose at this point. We would prefer to use MongoDB for all application and system development projects. Our preference to use MongoDB for development is based on ease of use, an emphasis on a code first approach for projects going forward, and built-in scalability and durability. Have you upgraded to MongoDB 3.2? What most excites you about this release? We’ve been developing the solution using MongoDB 3.0.x. We are actively migrating the database to version 3.2.1, and the production deployment will use 3.2.1. The most exciting features of MongoDB 3.2 for us are the BI connector, document validation, $lookup, and WiredTiger's in-memory option. We feel the biggest value add to our clients are the BI connector and the in-memory storage engine. The BI connector will allow our clients’ BI environments to integrate directly with the solution we are building, eliminating the need to write ETL processes from MongoDB to a BI environment. The in-memory storage engine will increase performance with read operations, which will reduce latency with API requests. Anything to increase overall performance is a plus. What advice would you give someone who is considering using MongoDB for their next project? I would highly recommend allocating a budget for MongoDB’s professional services to help with operations, deployment, and schema modeling. The value gained with their best practices approach really reduces learning curves and POC time. Coming from a SQL world, prepare ERDs and break the ERDs into schema designs. This approach will help bridge team members from a relational to a non-relational data store. Take a top-down development approach as it will uncover access patterns that may help with schema modeling. Thank you for sharing your MongoDB experiences with us! If you’re comparing MongoDB with relational databases, read our RDBMS to MongoDB Migration Guide to learn more. Read the RDBMS to MongoDB Migration Guide About the Author - Eric Holzhauer Eric is a Product Marketing Manager at MongoDB.
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, MongoDB Realm, the mobile database within the data platform, supports offline usage and syncing to ensure there is never data loss or functionality 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.