Resources

What's Driving Next-Generation Data Platform Adoption in Financial Services in APAC with Capgemini, AWS, and MongoDB

Discussion with Capgemini, AWS, and MongoDB into Forrester's global data platform study Data is recognized as a core asset to drive customer growth and innovation but the legacy technology that still underpins many organizations is not built to support today’s requirements. Not only is this infrastructure costly and complex, it doesn’t support the diversity of workloads and functions that modern applications require. To overcome these challenges, organizations are increasingly adopting an integrated data platform that offers a seamless developer experience, runs anywhere, and scales to meet growing business needs. To better understand how such data platforms are being used, MongoDB commissioned Forrester Consulting to conduct a study questioning global IT decision makers at financial services and fintech organizations. Watch this webinar with Capgemini, AWS, and MongoDB industry experts to learn: The business problems that are triggering financial institutions to rethink their approach to data in APAC How data platforms are currently being used in the financial services industry and what is driving their adoption The impact of legacy infrastructure and the different modernization approaches organizations can take to overcome their challenges Presenters: Wei You Pan Principal, Financial Services Industry Solutions at MongoDB Richard Caven Worldwide Banking Specialist, Amazon Web Services (AWS) Kapil Arora Senior Director at Capgemini James Hancock Senior Field Marketing Manager at MongoDB [Moderator] We hope you enjoy the webinar, if you would like to download the report, you can do so here.

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Atlas Search Webinar (English)

Atlas Search combines the power of Apache Lucene - the technology behind the world’s most popular search engines - with the developer productivity, scale, and resilience of MongoDB Atlas to make it easier than ever to integrate fast, relevance-based search capabilities into all of your MongoDB applications. During this webinar, we searched through different data types, including text, numbers, dates, and geoJSON while exploring a variety of search capabilities. Watch this recording to learn: How full text search compares to standard database querying How Atlas search differs from other full text search implementations An overview of the Atlas Search architecture Walkthrough of Atlas Search capabilities Demos of how to build and leverage Atlas Search indexes Showcasing sample applications built using Atlas Search

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Run Applications Anywhere with MongoDB Atlas Webinar Hong Kong

No one cloud infrastructure delivers all things to all people. Cloud vendors offer different blends of service-level agreements, availability, security architectures, pricing, tools, and resources for various needs. An increasing number of enterprises will cherry-pick among the various vendors to find the best combination of features for each specific workload. Where we get into MongoDB Cloud is the fact that with MongoDB Atlas, we deliver the database as a fully managed cloud service in nearly 100 regions worldwide across AWS, GCP, and Azure. Multi-cloud clusters in MongoDB Atlas, our globally distributed developer data platform, take the concept a step further by enabling a single application to use multiple clouds simultaneously. In this presentation, you will learn with multi-cloud clusters, how data is easily distributed across different public clouds, enabling data mobility and resilience without the complexity of manual data replication. The presentation was conducted in Cantonese.

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Transforming Customer Experience With Mongodb Atlas Search

Full-text search is essential for modern applications, but building it is hard. Developers either try to: Contort their database to handle search queries, quickly running up against feature limitations and performance overhead. Bolting on specialized search engines to their database, dramatically increasing the complexity of their application infrastructure. MongoDB Atlas Search gives you a much better way. It combines the power of Apache Lucene — the same technology underpinning the world’s most popular search engines — with the developer productivity, scale, and resilience of the MongoDB Atlas database. A couple of API calls or clicks in the Atlas UI and you instantly expose your data to sophisticated, relevance-based search experiences that boost engagement and improve customer satisfaction. Download this whitepaper to learn more about challenges of implementing search today and how that’s transformed with Atlas Search. We’ll discuss the ideal use cases for Atlas Search, along with those requirements where you may be better served considering alternative approaches. We’ll wrap up with how you can get started with Atlas Search today.

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April 12, 2023

Built-in, not bolt-on security: Unpacking vital security features in MongoDB Atlas for Government

Time: 12:00PM - 1:00PM ET Security is a non-negotiable when it comes to working in the public sector. Government agencies and contractors are trusted with sensitive data every day, and must balance protection of that data with the need to leverage that data for innovation. Using solutions that are secure by default is critical for public sector organizations, particularly in light of recent comments by Cybersecurity and Infrastructure Security Agency Director Jen Easterly. “We have to have [multi factor authentication] by default. We can't charge extra for security logging and [single sign-on],” Easterly said. “We need to ensure that we're coming together to really protect the technology ecosystem instead of putting the burden on those least able to defend themselves.” MongoDB Atlas for Government (US) ensures government agencies can modernize without compromising on data security. In this session, data security experts will break down: Atlas for Government’s new FedRAMP Moderate Authorization Key built-in security features including field-level encryption, role-based access management, network isolation, and more Strategies for modernizing while keeping data secure

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Thales eSecurity

Thales eSecurity is a leader in advanced data security solutions and services that deliver trust wherever information is created, shared or stored. We ensure that the data belonging to companies and government entities is both secure and trusted in any environment – on-premises, in the cloud, in data centres or big data environments – without sacrificing business agility. Thales provides everything an organisation needs to protect and manage its data, identities and intellectual property, and meet regulatory compliance – through encryption, advanced key management, tokenisation, and privileged-user control and high-assurance solutions. Security professionals around the globe rely on Thales to confidently accelerate their organisation’s digital transformation. Thales eSecurity is part of Thales Group. The Vormetric Data Security platform from Thales eSecurity for MongoDB provides transparent encryption, key management, privileged user access control, and security intelligence. Vormetric can monitor and block non-database users or processes from accessing or viewing the database in a MongoDB environment. Try out Vormetric at the AWS Big Data and Security Test Drive Labs . Fill out the form on this page to download our solutions brief and learn more.

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Dynamic Schema Design

Schema design determines the way an application handles its data. With traditional relational databases, you must define your schema before you can add any data. This inflexibility means you can’t change your schema as your data, application requirements or business evolves. In today’s world hyper-competitive, global business environment, this can hamper your efforts to innovate and stay on top of the competition. NoSQL databases arose to address this limitation by allowing you to insert data without a predefined schema. Because of this, you can easily make changes to an application without interruption. The result is more reliable code integration, faster development, and database administration time. MongoDB provides a document data model that lets you store and combine any type of data while also offering sophisticated data access and rich indexing features. With MongoDB, you don’t have to reinvent the wheel every time your business requirements change or evolve over time. To learn more about MongoDB’s dynamic schema design download the white paper or contact us.

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Evaluating Database Models

When you’re in the design phase of an application, evaluating database models is a critical step in the process. The database model determines the way an application handles data, directly affects the application’s performance and the ability to adapt to changing business requirements. In recent years, new data models have come about as part of the wave of NoSQL databases. These data models were designed to be flexible in order to tackle the large volume and variety of data typically generated by Big Data applications. In contrast, the data models in relational databases are inflexible and ill equipped to accommodate the way applications process data today. When you choose a newer, flexible database model, you benefit from: Being able to change your data model over time to suit your evolving needs Greater efficiency from not having to make time-consuming updates to the existing data in your system Being able to combine data from multiple sources to create a single view of your data MongoDB leads the pack of new database models by offering a document data model that allows for iterative and adaptive data modeling. A flexible schema design lets you incorporate new data into your application without a predefined schema. This allows you to iterate on your application with no interruption or downtime. MongoDB is a database built for today’s always-on, Big Data applications. With MongoDB, you can simplify your design, dynamically modify the database model, and cut down on overall development time. Contact us or download the white paper to learn more about our flexible data model.

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Internet of Things Applications

The future has arrived. Is your database prepared? Technology companies are doing some awe-inspiring things with Internet of Things (IoT) applications. IoT describes technology which connects physical assets and devices together to share information and make life easier and more convenient. IoT devices are processing volumes of data previously unimagined. Bosch, for example, is harnessing data to use in a range of industrial internet of things applications including manufacturing, automotive, retail, and energy. With these sensor-enabled objects, futuristic scenarios have come alive in the ways previously thought impossible. New revenue opportunities abound but only if companies can wrangle that data into something meaningful. Enter MongoDB, the world’s most popular NoSQL database, to help you make sense of sensor data, building internet of things applications never before possible. All this in less time and with less cost than with alternative technologies. The advantages of creating an internet of things application with MongoDB: Document data model. With MongoDB, you can manage and incorporate data in any structure. This allows for you to launch and iterate on your application without having to start from scratch to meet evolving requirements. Inexpensively scale. IoT applications process great volumes of data through sensors so your system will need to scale quickly and cheaply. One of the advantages of MongoDB is the ability to scale out on inexpensive commodity hardware in your data center or in the cloud. Analyze any kind of data with MongoDB. Real-time analysis within the database means you don’t get the time delay you normally would processing data through an expensive data warehouse system. Internet of things applications can spell revolutionary change for your business. Learn more about why IoT is only possible with newer Big Data technology like MongoDB. Download our white paper, Why NoSQL Databases for the Internet of Things: Machina Research, for more insight into the challenges and opportunities for IoT in a rapidly evolving landscape.

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Managing Distributed Data

Today’s generation of databases offers application developers lower cost, greater efficiency, and superior performance in comparison to its more traditional relational counterparts. A key driver behind the lower cost is the ability to scale out your system over commodity hardware. Older relational database technology, on the other hand, is expensive to scale because you need to buy a bigger server to meet the greater volume demand. MongoDB is the leader in a new generation of databases that are designed for scalability. With a technique called “sharding” you are able to easily distribute data and grow your deployment over inexpensive hardware or in the cloud. One of the benefits of scaling with MongoDB is that sharding is automatic and built into the database. This relieves developers of having to build in sharding logic into the application code to scale out the system. Scaling a database system is complex but MongoDB makes it easy. Find out more about the database developers love and the one that enterprises rely on to grow their businesses. Download our white paper today.

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Managing Unstructured Data

Data was pretty straightforward in the days before online applications and mobile devices. Databases processed data in a pre-defined structure of rows and columns contained in tables. This was totally upended with the rise of unstructured data in recent years. By some accounts, unstructured data – think emails, SMS texts, videos, social media posts – makes up more than 95% of all data generated today. The old way of managing data in relational databases, then, is encountering great limitations. Enter NoSQL databases to pick up the challenge of managing unstructured data. MongoDB is the top NoSQL database solution according to DB-Engine rankings, and MongoDB has been downloaded 40 million times and counting. MongoDB’s document data model is particularly well suited for storing unstructured data. It stores all related data together within a single document, and doesn’t require data to fit neatly into the rigid structure of relational rows and columns. Unstructured data can represent both a challenge and an opportunity. Many enterprises have used MongoDB to build applications that could never have been built with relational technology. Learn more about how you can shine by making productive use of your unstructured data and download our whitepaper today.

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MongoDB Benchmark

Application downtime or slow performance could spell disaster for any business. It is essential for companies to proactively monitor and work to ensure high availability and high performance for applications. As part of this strategy, operations teams should establish performance requirements that are continuously monitored to ensure the needs of the business are being successfully delivered to customers. At MongoDB, we take database performance very seriously, and we work to make each release faster and more resource efficient. With MongoDB 3.0, we made major advances in database performance and compared this release to prior releases to understand just how far we had come. Using YCSB, a popular testing framework for database performance, we evaluated a number of workloads on MongoDB 2.6 and MongoDB 3.0. We found greatly enhanced performance over the previous version – anywhere between 7 to 10 times better performance. United Software Associates, an independent third party, also tested MongoDB performance against other database technologies. In their benchmark testing, MongoDB far exceeded other databases in terms of throughput and latency across a number of configurations. There is a reason why MongoDB is the leading database with 40 million downloads and the highest ranking from DB-Engines among NoSQL databases. Find out more about how MongoDB outperforms other leading databases by download the comparative benchmarks.

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