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Ventana Research's Latest Report Highlights MongoDB's Role as a Cloud Data Platform Provider

Ventana Research, a market advisory and research firm, recently published an Analyst Perspective on MongoDB, noting that MongoDB and its application data platform provide businesses the ability to accelerate development and data-driven decision-making. As Ventana Research explains the evolution from traditional databases to modern, cloud-based application data platforms, the study covered multiple trends related to both the present and future of data platform software. We have identified six key trends from MongoDB that were represented in the Ventana Research Analyst Perspective. Non-relational, or NoSQL, databases are on the rise . We see this as evidence of an unprecedented, widespread change in how businesses perceive and use their databases. Cloud-based services and products are rapidly gaining popularity . Given the rise of real-time, data-driven applications, organizations are relying more and more on the flexibility, availability, and functionality of cloud-native data platforms. Such products are ideal for quickly building competitive products, delivering highly personalized experiences, and improving business agility. As a result, operational database requirements will only become more demanding . As applications become more advanced, databases will become a pivotal part of an organization’s success — or failure. We believe that in order to keep up with their applications (and their competition), companies require a comprehensive, powerful application data platform like MongoDB Atlas. Convergence is the name of the game . As companies seek out new and better operational data platforms, both relational and non-relational database providers will venture into areas that were traditionally dominated by their competitors. Examples include non-relational databases (like MongoDB) adding relational features like ACID transactions, or relational databases offering compatibility for non-relational data models like graphs or documents. Companies are increasingly opting for hybrid and multi-cloud models . MongoDB Atlas’ multi-cloud clusters enable users to leverage exclusive provider features (like Google Cloud’s AI tools), improve availability in geographic regions, or migrate data across clouds with no downtime. Non-relational, cloud-native databases are becoming more powerful — and more attractive to customers . Thanks to convergence and competition, non-relational databases are becoming ever more capable. Their advancements include real-time analytics, rich visualizations, and mobile data sync and storage. Read Ventana Research Analyst Perspectives to gain insight into the current data landscape and the possibilities of tomorrow. Updated January 17, 2022.

January 12, 2022
News

MongoDB World 2022 Call for Speakers - 5 Tips For a Successful Submission

MongoDB World is back in New York City on June 7-9 2022, and Call for Speakers is open until January 18! We are looking for speakers who can inspire attendees by introducing them to new technologies, ideas, and solutions. If your team is building amazing things with MongoDB, we want to hear about it. Are you passionate about a topic but have no speaking experience? Not a problem. We welcome first-time speakers and encourage speakers from underrepresented groups in technology to apply. We offer outline workshops, slide design training, and one-on-one coaching with a professional speaker coach for all accepted speakers. Additionally, we have an anonymous grading process and your speaker information is hidden from the committee during grading, so we grade the submissions based on content only. Our reviewers have to review a lot of submissions every year. Here are 5 tips for a submission that will stand out from the crowd: Review sessions from previous events — Take a look at our past talks at MongoDB.live 2021 to get an idea of what types of talks we accepted. We also love to hear about topics that are new or unique from what we already have. Have a simple and clear session title — The title is the first thing that our reviewers will see. Puns, creative wordplay, and “hooks” in titles are okay, but make sure that if all someone knew was the title, they still would have some idea what the presentation is about. Include key takeaways in your description — The description is what will convince us to accept your talk. Use the description to explain what the problem is. How did you solve it? Include tons of examples of what you’d talk about. For help developing your description check out the free MongoDB University course and learn more about writing abstracts here . Tell us more in the notes section — Use the notes section to explain the details of your talk in a bit more conversational way. Share your experience with the problem, give us the outline of your talk, or explain why MongoDB World would be less without your talk. Select the right track and session format — We have 8 tracks at MongoDB World this year and 3 different session formats (session, lightning talk, tutorial). Make sure to read the descriptions for each track and submit to the right one for your talk. We review every talk and do our best to move talks to other tracks, but sometimes they can fall through the cracks. Selecting the right track and session format will ensure that your talk is reviewed properly. Call for Speakers is open until January 18, 2022. Don’t miss your chance to be a part of MongoDB World and submit your proposal today! Learn More

January 4, 2022
News

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 application 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 as the modern application data platform. 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.

November 9, 2021
News

Congratulations to the 2021 Innovation Award Winners!

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 the company received entries across dozens of industries, ranging from disruptive, emerging start-ups to industry-leading global enterprises. We are thrilled to announce the 12 winners who are being honored this year during MongoDB.live. William Zola Award: Michael Höller - An independent software architect, system integrator, and backend developer, Michael is the first MongoDB Champion to earn the rare Evergreen forum badge for his unwavering support of the MongoDB Community. Dual-certified as both a MongoDB Developer and DBA, Michael generously shares his expertise with community members of all levels in the MongoDB forums. He also organizes the DACH Virtual Community User Group, and even finds time to #BuildTogether with MongoDB employees on presentations and in chats during online streams. Michael is one of the first-timers, consulting on MongoDB projects since 2014. Customer-first Award: Luma Health - As COVID-19 took the world by storm, Luma Health jumped into action to partner with health systems and providers to leverage their platform to run some of the largest mass vaccination sites and help clinics scale from hundreds to thousands of appointments, ultimately leading to nearly 2 million vaccination appointments. Data for Good Award: Journey Foods - This company solves food science and supply chain inefficiencies with software in order to help companies feed 8 billion people better. To date, Journey Foods has established a database of over 11 billion ingredient insights. From Batch to Real Time Award: CSX - A leading provider of transportation and supply chain solutions, CSX is redefining freight rail. Embracing event-driven architecture, the company has improved engagement with safety information produced by Positive Train Control (PTC) systems by putting PTC data on MongoDB. Leveraging MongoDB, CSX receives the data real-time – enabling smarter and faster decision making and better ensuring safety regulations are met for the company’s around-the-clock operations. Front Line Heroes Award: Ahmad Awais for The “CORONA CLI” Project - Awais built a CLI command-line tool to track COVID-19 in March 2020. As COVID-19 spread, the project termed “corona-cli” became the number one trending repository on GitHub. To date, this project has served several billions of API requests making COVID stats accessible throughout the world with 53 different releases and extensive functionality built/contributed by 15+ developers. Going Global Award: Riot Games - Founded in 2009 to change the ways games were developed, Riot has created the most-played PC game in the world and expanded to 20+ offices worldwide in only 12 years. A game platform developer and his team migrated their data to MongoDB Atlas to manage B2B billing and player IP validation data for all of their games globally. Industry Transformation Award: American Airlines - As a network air carrier, American’s purpose is to care for people on life’s journey. During COVID-19, American Airlines passionately pursued efficiencies, particularly those enabled by technology. American Airlines created an operational data layer on MongoDB in the cloud for critical flight information, which enabled other services to move to the cloud and consume data from the modern cloud-based data fabric. Jackpot Award: Cisco Systems - Cisco is the worldwide leader in technology that powers the Internet. This global brand completed the Cloud native migration of its highly critical Commerce Quoting platform, which serves more than 225K users and 4M application hits daily worldwide. The result has been no application downtime for releases, improved performance, lower TCO, and significantly better developer productivity. Savvy Start-Up Award: Blerp - The audio expression platform that makes it easy to enhance any moment with sound clips. Millions of Blerps are being shared on their two largest integrations on Twitch and Discord. Unbound Award: Yodel - Yodel is an independently owned parcel carrier, delivering around 190 million parcels each year for many of the UK’s leading retailers and businesses. An early adopter of Realm Sync following its GA release in February 2021, Yodel uses MongoDB to sync parcel-scanning data from employee devices up to Atlas - and in the opposite direction, pushing down large data volumes to devices via the MongoDB Kafka Connector. By streamlining the process of scanning parcels and reducing the time drivers need to spend in service centers, Yodel expects to achieve increased productivity and cost savings. Certified Professional of the Year Award: Sydney Herrera - After becoming certified and while assisting a large governmental organization in a mainframe modernization effort - which involved transforming multiple massive, disparate mainframe datastores into a cohesive and application-focused MongoDB data warehouse, Sydney was faced with the challenge of assisting developers with building efficient applications. He created a tool called proactive query analyzer (PQA) that was rolled out into the organization. PQA is an automated tool that analyzes queries sent to MongoDB and provides feedback and suggestions before queries are implemented to aid developer teams. For the People Award & Innovator of the Year Award: The Department for Work and Pensions (DWP) is the UK’s biggest public service department responsible for distributing over £190 billion annually in welfare, pensions and child maintenance to over 20 million citizens. With an unprecedented spike in demand due to the COVID-19 crisis, the Universal Credit platform was able to scale seamlessly, underpinned by MongoDB databases, to meet the tenfold spikes in claims from people who needed DWP’s support. The information contained in the above descriptions was provided by the relevant award winners or obtained from publicly available information.

July 14, 2021
News

Fine-Tune Relevance in MongoDB Atlas Search with Function Scoring and Synonyms

MongoDB Atlas Search is an embedded full-text search solution in MongoDB Atlas that gives developers a seamless and scalable experience for building fast, relevance-based application features. We announced its general availability last year at MongoDB.live 2020 and over the past year we’ve introduced many new features, including a visual index builder, search query tester, custom analyzers , and wildcard path queries . This year at MongoDB.live 2021 , we’re excited to highlight two new capabilities that help developers tune the relevance of search results. See how easy it is to get started with MongoDB Atlas Search in this demo video by Marcus Eagan, Senior Product Manager for Atlas Search. Building relevance into search results Understanding the behavior of your users is essential when thinking about search result relevance. People don’t always tell you what they want, and they sometimes use words or phrases that don’t match your content exactly. To cover these scenarios, you can use full-text search features like function scoring and synonyms. Influence search rankings with function scoring There are often multiple factors that influence how search results should be ranked. For example, let’s say you have a restaurant finder application. The explicit inputs are things like the user’s location and what they’re searching for, but what’s implied is that they likely want to see highly rated restaurants or ones with more reviews. What’s Cooking: a sample restaurant finder application using MongoDB Atlas Search Function scoring allows you to influence the order of results returned by manipulating the score of each result. In Atlas Search, that means you can use a numeric field in a document and apply a mathematical expression to it. For example, you might want to increase the score of restaurants that are sponsored or have higher star ratings. This can easily be accomplished within the same search query by simply adding the function option to the score parameter of your query. Learn more about how to use function scores in our developer tutorial . Show results for more search queries with synonyms Synonyms are often used to define terms that are semantically similar to each other to improve search results. For example, someone searching for “noodles” might want to find results for “spaghetti”, “chow mein”, or “pad thai”. Synonyms can also help with typos, especially on mobile and small keyboards. In Atlas Search, you can define collections of synonyms for a search index via the API. Synonyms can be explicit (one-way) or equivalent (two-way). Explicit synonyms are good for defining relationships between terms that are subsets of each other, like the noodle example above: “spaghetti”, “chow mein”, and “pad thai” are all explicit synonyms for “noodles”, but not each other (you don’t want results for “chow mein” in a search for “spaghetti”). Equivalent synonyms are often used for terms that have regional variations or are otherwise interchangeable both ways, like soda and pop, or Kleenex and tissues. What's next for Atlas Search Developers are increasingly turning to full-text search to make content more discoverable and relevant for application end users. With Atlas Search, we hope to not only make building full-text search easier, but also more powerful and expressive. Join our community to ask questions and find out what other developers are building with Atlas Search and let us know what you think we should build next in our feedback forums .

July 13, 2021
News

Introducing Serverless Instances on MongoDB Atlas, Now Available in Preview

Since we first launched MongoDB Atlas in June 2016, we’ve been working towards building a cloud database that not only delivers a first-class developer experience, but also simply just works: no setup, tuning, or maintenance required. Over the years, this has led to features like auto-scaling and click-to-create index suggestions , along with numerous optimizations to our automation engine. We’re excited to announce that we’re one more step closer to realizing this vision with the introduction of serverless databases on MongoDB Atlas . Think less about your database, and more about your data Serverless computing and NoOps have emerged as popular trends in modern application development. Cloud functions are commonly used to power business logic in applications, and many teams rely on completely automated IT operations. The appeal of serverless technology is hard to deny: elastic scaling eliminates the need for upfront resource provisioning and ongoing maintenance, and consumption-based pricing means paying only for resources that are used. It abstracts and automates away many of the lower-level infrastructure decisions that developers don’t want to have to learn or manage so they can focus on building differentiated features. When it comes to databases, compute and storage resources have traditionally been tightly coupled. Applying a serverless model to databases means decoupling them and changing the way engineering teams think about infrastructure. Rather than asking a developer to predict an application’s future workload patterns, break them down into individual resource requirements, and then map them to arbitrary units of database instance sizes, serverless databases offer a much simpler experience: define where your data lives, and get a database endpoint you can use. This not only streamlines the database deployment process, it also eliminates the need to monitor and adjust capacity on an ongoing basis. Developers are free to focus on thinking about their data rather than their databases, and leave the lower-level infrastructure decisions to intelligent, behind-the-scenes automation. Serverless instances on MongoDB Atlas All customers now have the ability to create a serverless database on MongoDB Atlas with the introduction of serverless instances , announced at MongoDB.live 2021 . It’s incredibly easy to get started: simply choose a cloud region and you’ll receive an on-demand database endpoint for your application. Serverless instances always run on the latest MongoDB version so you never have to worry about backwards compatibility or upgrades. You can view and manage them using the same UI and API as your existing database deployment on Atlas (i.e., clusters), and they come with end-to-end security, continuous uptime, metrics, alerts, and backups. Watch this demo of how to create a serverless instance on MongoDB Atlas This new deployment type will be available in preview, so it doesn’t yet support all of the features and capabilities available on clusters today. It’s ideal for infrequent or sparse workloads, or development and testing workloads in the cloud. If you’re running a high-throughput production workload, dedicated clusters are still the recommended deployment option. A hands-free database experience This is the first of many releases, and we have an ambitious roadmap ahead. We will continue to invest in making working with data ever more seamless and delightful for developers, from adding support for newer Atlas capabilities like full-text search and native visualizations , to even more intelligent automation and optimization. Create your own serverless instance on MongoDB Atlas. Try the Preview If you have feedback or questions, we’d love to hear them! Join our community forums to meet other MongoDB developers and see what they’re building with serverless instances. What's next for MongoDB Atlas Serverless instances are just one of many new additions to Atlas that we hope will make developers’ lives easier. Earlier this year, we added index removal suggestions to Performance Advisor and released a quick start for creating and managing clusters via the command line with the MongoDB CLI . We are also working on integrations with Vercel and Netlify , two popular serverless application platforms, to give developers an easy way to get started on MongoDB Atlas. What would make your development experience better on MongoDB Atlas? Share your feature requests in our feedback forums .

July 13, 2021
News

Launched Today: MongoDB 5.0, Serverless Atlas, and the Evolution of our Application Data Platform

Today we welcome you to our annual MongoDB .Live developer conference. Through our keynote and conference sessions we'll show you all the improvements, new features, and exciting things we've been working on since last year’s conference. What I want to do in this blog post is provide you with a summary of what we are announcing, and resources to help you learn more. While it's easy to focus on what we are announcing at this year's event, we actually started out on this journey 12 years ago by releasing the world’s most intuitive and productive database technology to develop with — MongoDB. And we believe the applications of the NEXT 10 YEARS will be built on data architectures that continue to optimize for the developer experience, allowing teams like yours to innovate at speed and scale. So how are we building on this vision? Today I am incredibly proud to announce three big things: The General Availability (GA) of MongoDB 5.0, the latest generation of our core database. It includes native support for time series workloads, new ways to future-proof your applications, multi-cloud privacy controls, along with a host of other improvements and new features. The preview release of serverless instances on MongoDB Atlas, which makes it even easier for development teams who don’t want to think about capacity management at all to get the database resources they need quickly and efficiently. Major enhancements to Atlas Data Lake, Atlas Search, and Realm Sync, which allow engineering teams to reduce architectural complexity and get more value out of their data by leveraging a unified application data platform. MongoDB 5.0 GA MongoDB 5.0 is the latest generation of the database most wanted by developers . Our new release makes it even easier to support a broader range of workloads, introduces new ways of future-proofing your apps, and further enhances privacy and security. This major jump in version number from MongoDB 4.4 – our prior GA version – to 5.0 reflects a new era for MongoDB's release cadence: We want to get new features and improvements into your hands faster. Starting with MongoDB 5.0, we will be publishing new Rapid Releases every quarter, which will roll up into Major Releases once a year for those of you that want to maintain the existing annual upgrade cadence. You can learn more about the new MongoDB release cadence from our blog post published last October. Digging into MongoDB 5.0, here is what’s new and improved: Native Time Series Designed for IoT and financial analytics, our new time series collections, clustered indexing, and window functions make it easier, faster, and lower cost to build and run time series applications, and to enrich your enterprise data with time series measurements. MongoDB automatically optimizes your schema for high storage efficiency, low latency queries, and real-time analytics against temporal data. Running your time series applications on our application data platform eliminates the time and the complexity of having to stitch together multiple technologies yourself. You can manage the entire time series data lifecycle in MongoDB – from ingestion, storage, querying, real-time analysis, and visualization through to online archiving or automatic expiration as data ages. Time series collections can sit right alongside regular collections in your MongoDB database, making it really easy to combine time series data with your enterprise data within a single versatile, flexible database – using a single query API to power almost any class of workload. Our new time-series collections blog post gives you everything you need to get started. Future-proof with the Versioned API and Live Resharding Starting with MongoDB 5.0, the Versioned API future-proofs your applications. You can fearlessly upgrade to the latest MongoDB releases without the risk of introducing backward-breaking changes that require application-side rework. Using the new versioned API decouples your app lifecycle from the database lifecycle, so you only need to update your application when you want to introduce new functionality, not when you upgrade the database. Future-proofing doesn’t end with the Versioned API. MongoDB 5.0 also introduces Live Resharding which allows you to easily change the shard key for your collections on demand – with no database downtime – as your workload grows and evolves. The way I like to think about this is that we’ve extended the flexibility the document model has always given you down to how you distribute your data. So as things change, MongoDB adapts without expensive schema or sharding migrations. Next-Gen Privacy & Security MongoDB’s unique Client-Side Field Level Encryption now extends some of the strongest data privacy controls available anywhere to multi-cloud databases. And with the ability in 5.0 to reconfigure your audit log filters and rotate x509 certificates without downtime you maintain a strict security posture with no interruption to your applications. Run MongoDB 5.0 Anywhere MongoDB 5.0 is available today as a fully-managed service in Atlas . You can of course also download and run MongoDB 5.0 on your own infrastructure, either with the community edition of MongoDB, or with MongoDB Enterprise Advanced . The Enterprise Advanced offering provides sophisticated operational tooling via Ops Manager, advanced security controls, proactive 24x7 support, and more. MongoDB Ops Manager 5.0 enhancements include: Support for the automation, monitoring, and backup/restore of MongoDB 5.0 deployments. Improved load performance with parallelized client-side restores. A quick start experience for deploying MongoDB in Kubernetes with Ops Manager. And lastly, a guided Atlas migration experience that walks users through provisioning a migration host to push data from their existing environment into the fully managed Atlas cloud service. You can learn more about MongoDB 5.0 from our What’s New guide . New to MongoDB Atlas — Serverless Instances (Preview) We want developers to be able to build MongoDB applications without having to think about database infrastructure or capacity management. With serverless instances on MongoDB Atlas, now available in Preview, you can automatically get the database resources you need based on your workload demand. It’s really simple: the only decision you need to make is the cloud region hosting your data. After that, you’ll get an on-demand database endpoint that dynamically adapts to your application traffic. Serverless instances will support the latest MongoDB 5.0 GA release, Versioned API, and upcoming Rapid Releases so you never have to worry about backwards compatibility or upgrades. Pay only for reads and writes your application performs and the storage resources you use (up to 1TB of storage in preview) and leave capacity management to MongoDB Atlas’s best-in-class automation. We invite you to try it out today with a new or existing Atlas account. And the Preview release is just the beginning – we will be working with partners such as Vercel and Netlify to deliver an integrated serverless development experience in the coming months. In the longer term, we will continue to evolve our cloud-native backend architecture to abstract and automate even more infrastructure decisions and optimizations to deliver the best database experience on the market. The New MongoDB Shell GA The new MongoDB Shell has been redesigned from the ground up to provide a modern command-line experience with enhanced usability features and powerful scripting environment. It makes it even easier for users to interact and manage their MongoDB data platform, from running simple queries to scripting admin operations. A great user experience, even on a command-line tool, should always be a major consideration. With the new MongoDB Shell we have introduced syntax highlighting, intelligent auto-complete, contextual help and useful error messages creating an intuitive, interactive experience for MongoDB users. Check out this blog post for more information. MongoDB Charts and Atlas Data Lake: Better Together MongoDB Charts intuitive UI and ability to quickly create & share charts and graphs of JSON data is now integrated with Atlas Data Lake . You can now easily visualize JSON data stored in Amazon AWS S3 without any data movement, duplication or transformation. Furthermore, you can run Atlas Data Lake’s federated query to blend data across multiple Atlas databases and AWS S3, and visualize the results with Charts. By adding Atlas Data Lake as a data source in Charts, you can discover deeper, more meaningful insights in real time. Check out this blog post for more information. Atlas Search — More Relevance Features It’s incredibly important for modern applications to deliver fast and relevant search functionality: it powers discoverability and personalization of content, which in turn drives user engagement and retention. Atlas Search , which delivers powerful full-text search functionality without the need for a separate search engine, has several new capabilities for building rich end user experiences. We’ve recently added support for function scoring, which allows teams to apply mathematical formulas on fields within documents to influence their relevance, such as popularity or distance — e.g. closer restaurants with more or better reviews will show up higher in a list of results. In addition, you can now define collections of synonyms for a particular search index. By associating semantically equivalent terms with each other, you can respond to a wider range of user-initiated queries in your applications. Realm Realm lets you have simple, powerful local persistence on mobile phones, tablets and IoT devices like Raspberry Pi. The Realm SDKs provide a set of APIs that let developers store and interact with native objects directly, reducing the amount of code required as there is no need for ORMs or learning cryptic database syntax. In addition, we made MongoDB Realm Sync generally available earlier this year, making it easy to synchronize data between local storage on your devices and MongoDB Atlas on the backend. No need to worry about networking code or dealing with conflict resolution as we handle all of that for you. Today, we’re excited to announce support for Unity. You can now use Realm to store your game data, like scores and player state, and sync it automatically across devices. Realm's support for Unity is now Generally Available and ready for production workloads. We're also investing in support for more cross-platform frameworks — the Kotlin Multiplatform and Flutter/Dart SDKs are now both available in Alpha. And finally, the team is working towards Realm Flexible Sync, a new way to synchronize data with more granular control. Flexible Sync will allow you to — Build applications that respond dynamically to user's needs. Let your end users decide what data they need, and when. Use more precise permissions that can adapt over time. Check out this dedicated blog on our upcoming plans for Flexible Sync to learn more. Getting Started With everything we announced today, you can imagine it was a packed keynote! And there is so much more that we didn’t cover. You can get all of the highlights from our new announcements page where you will also find all the resources you need to get started.

July 13, 2021
News

MongoDB Atlas for Government

We are pleased to announce the general availability of MongoDB Atlas for Government, which is an independent environment of our flagship cloud product MongoDB Atlas that’s built for US government needs. It will allow federal, state, and local governments as well as educational institutions to build and iterate faster using a modern database-as-a-service platform. The service is available in AWS GovCloud (US) and AWS US East/West regions. We are also pleased to announce that MongoDB Atlas for Government has been approved as FedRAMP Ready . FedRAMP Ready indicates that a third-party assessment organization has vouched for a cloud service provider’s security capabilities, and the FedRAMP PMO has reviewed and approved the Readiness Assessment Report. MongoDB Atlas for Government Highlights: Atlas for Government clusters can be created in AWS GovCloud East/West or AWS East/West regions. Atlas for Government clusters can span regions within AWS GovCloud or within AWS (but not across those two environments). Atlas core features such as automated backups, AWS PrivateLink, AWS KMS, federated authentication, Atlas Search, and more are fully supported Applications can use client-side field level encryption with AWS KMS in GovCloud or AWS East/West. Getting Started and Pricing: MongoDB Atlas for Government is available to Government customers or companies that sell to the US Government. You can buy Atlas for Government through AWS GovCloud or AWS marketplace . Of course, you can also work directly with MongoDB; please fill out this form and a representative will get in touch with you. To learn more about Atlas for Government, visit the product page , check out the documentation , or read the FedRAMP FAQ .

June 28, 2021
News

MongoDB Atlas Celebrates Five Years of Innovation in Data

Today we’re thrilled to celebrate the five-year anniversary of Atlas, MongoDB’s multi-cloud database platform. When we launched Atlas in 2016, we couldn’t have foreseen the impact it would have on both our customers and MongoDB as a company. MongoDB Atlas has allowed us to become an ever more trusted partner to our customers, playing a key role in their efforts to manage and mitigate risk. One of the insights that spurred the development of Atlas — that it should be easy to move your data into, out of, and between clouds — remains as groundbreaking today as it was five years ago. Thanks to our commitment to innovation, reliability, and security, Atlas’s customers include well-known companies such as Forbes , Toyota Material Handling , Pitney Bowes , and 7-Eleven . Sixty of the Fortune 100 and many of the world’s most innovative disruptors rely on Atlas to help them grow, become more efficient, gain insights from their data, and create superior customer experiences. Atlas has transformed MongoDB into a cloud-first company: Atlas’s revenue is growing at 73 percent a year and currently accounts for more than half of MongoDB’s revenue. We got a glimpse of the future in 2009 with the first production version of MongoDB. For years, developers struggled to build modern applications on top of decades-old relational databases. Using a JSON-based document model, MongoDB was exceptionally fast, scalable, flexible, and intuitive for developers. It was unusually proficient with both structured and unstructured data. The database’s very design pushed developers and engineers to think differently about how they worked with data. As our customers investigated new business models enabled by the cloud, we noticed two things about the way they were working with data. First, they were increasingly choosing to use MongoDB in the cloud rather than hosting it on premises. Second, our customers were gravitating toward managed services. If our customers were going to the cloud — and they were — we needed to be there too. Our goal was not only to become a cloud-native database, but also to provide developers with a superior platform so they could change the world with data — and employ all the cloud’s potential to do it. As a managed service, Atlas would free developers from the overhead of managing MongoDB themselves. By making data portable across the biggest public clouds, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure, it would free data from vendor lock-in. Developers and engineering teams could match the right cloud to the right workload in a few clicks and a few minutes without writing or rewriting code. Since Atlas shipped in 2016, it has gained more than 25,000 customers. We’ve dramatically improved its functionality, turning it into an even more powerful tool to fulfill our mission of making data stunningly easy to use. At its 2016 launch, Atlas was available in four AWS regions. The next year, we introduced cross-region replication. Within a single cloud, a customer could now enable cross-region deployments for even better availability guarantees. We launched global clusters in 2018, which made it easier to place data closer to the user and enabled our customers’ applications to run faster all over the world. MongoDB Atlas is now available in about 80 regions across AWS, Microsoft Azure, and GCP. Atlas customers can switch clouds as business requirements change to take advantage of pricing changes and make the best use of each cloud’s capabilities. Our broad reach also helps our customers comply with increasingly complex data sovereignty and localization requirements. We’ve pushed Atlas well beyond the ability to serve larger numbers of regions. In 2019 we acquired Realm , which makes data accessible no matter where your user is or how lousy their connectivity may be. The MongoDB Realm Mobile Database enables simple, powerful persistence on mobile devices so apps can work offline as well as they do online. Two years later, we released MongoDB Realm Sync, making it even easier to keep data in sync across users and devices and connect to the Atlas database on the backend. We also released MongoDB Atlas Search, which enables developers to create rich, relevance-based search without moving their data into a separate search engine. That was accompanied by MongoDB Atlas Data Lake, enabling developers to use federated queries to analyze data across tiers. In 2019 we introduced client-side field-level encryption, an industry-leading approach to security. It’s relatively common to encrypt data at rest or in transit, but client-side field-level encryption encrypts data while it’s in use. There’s no additional code for developers to write and no significant impact on performance, and applications can still query data. Client-side field-level encryption enables our clients to use managed services in the cloud with more confidence, because even those who support the underlying cloud infrastructure cannot decrypt the data. It also makes it easier to comply with increasingly common “right to be forgotten” mandates in contemporary privacy legislation. A user can be forgotten simply by destroying the associated encryption key, making their data unreadable and irrecoverable. In 2020, our development teams accomplished what had been their mission since the inception of Atlas: multi-cloud clusters. With multi-cloud clusters, MongoDB Atlas goes well beyond its promise — fulfilled years earlier — to work equally well in any of the public clouds. Multi-cloud clusters enable a single cluster to be in multiple clouds simultaneously, making it trivial to move data between them. We have big plans for the next five years, and we’re already getting started. Soon we’ll preview serverless instances on MongoDB Atlas, making it even easier for development teams to get the capacity they need, when they need it. You choose the region that hosts your data and we’ll do the rest, with an on-demand database endpoint that dynamically adapts to your application traffic. We’re also making it easier to support a broader range of workloads, offering new ways to future-proof apps, and continuing to improve security and privacy capabilities. We’ll be making major enhancements to Atlas Data Lake, Atlas Search, and Realm Sync, all of which reduce architectural complexity and allow our customers to get more value from their data with a unified application data platform. And we’ll be doing it all on an accelerated cadence. Starting with MongoDB 5.0, we’ll publish new releases every quarter for those who want to be on the fast track, and then rolling those up into annual Major Releases for those who want to stay on the current cycle. We expect the next five years to be just as exciting and innovative as the past five — if not more. We can’t wait to see you there. For more on Atlas's Five Year Anniversary, check out this video

June 28, 2021
News

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