The first version of the MongoDB database shipped in August 2009. The 1.0 release and those that followed shortly after were focused on validating a new and largely unproven approach to database design – built on a JSON-like document data model and layered onto an elastic and distributed systems foundation. Those early MongoDB releases attracted masses of adoption across startups and enterprises alike.
With early usage validating product/developer fit, the MongoDB engineering team’s focus shifted to Industrializing the system beyond a niche NoSQL database into the industry’s first application data platform. From operational and transactional workloads with integrated full-text search through to real-time analytics and mobile computing at the network edge, the MongoDB Atlas application data platform accelerates and simplifies how developers build with data for any class of modern application, all accessed via a unified API.
Developers have downloaded MongoDB more than 200 million times, and have consistently rated it as their most wanted database.
MongoDB 5.x with native time series collections optimized for IoT and financial apps; live resharding so you can change your shard key on-demand with no database downtime; distributed cross-shard JOINs and graph traversals for sophisticated analytics against live data, faster initial sync via file copy, new aggregation operators, and more.
The MongoDB Stable API future-proofs your applications. You can upgrade to the latest MongoDB releases without the risk of backward-breaking changes
Atlas Serverless instances (preview) automatically and dynamically scale to meet your workload and you pay only for the resources consumed
The MongoDB Atlas Data API (preview) provides a fully managed, REST-like API for accessing your Atlas data without the need for database drivers.
MongoDB 4.4 offering richer aggregations with UNION; streaming replication reducing data synchronization latency across a distributed database cluster by up to 50% ; hedged and mirrored reads for consistent low latency in the face of infrastructure failures
MongoDB Atlas Online Archive to automatically tier aged data from your database to fully managed, queryable object storage, optimizing scalability, performance, and cost
Realm Mobile Database & Sync, delivering best-in-class experiences at the edge of the network with an embedded mobile database and automated sync to MongoDB Atlas in the cloud, keeping data updated across users, devices, and your backend.
MongoDB Atlas multi-cloud clusters providing the ability to distribute data in a single cluster across multiple public clouds simultaneously, or move workloads seamlessly between them
MongoDB 4.2 bringing distributed, cross-shard ACID transactions for data integrity at global scale; client-side field level encryption providing some of the strongest privacy controls anywhere; on-demand materialized views for blazing fast analytics
MongoDB Atlas Search, combining the power of Apache Lucene with the Atlas platform, making it easy to build fast, relevant, full-text search on top of your data in the cloud.
MongoDB Atlas Data Lake, enabling you to quickly and easily query data in any format on Amazon S3 using the MongoDB Query API
MongoDB 4.0 with multi-document ACID transactions, making it even easier to address a complete range of use-cases with MongoDB and simplifying legacy database migrations
MongoDB Atlas Global Clusters, creating fully managed, globally distributed database deployments for low latency reads and writes anywhere, and data placement controls for regulatory compliance.
MongoDB Atlas enterprise security controls with LDAP integration; bring-your-own KMS for encrypting data at-rest; and granular event audit logging
MongoDB Charts providing a modern data visualization and analytics tool that allows you to easily create, share, and embed visualizations from Atlas and Atlas Data Lake
Fully-managed MongoDB Atlas database service expanded from AWS to Azure and Google cloud, providing unmatched data distribution across all of the leading cloud providers
Further improved data integrity with schema validation to enforce a schema against your data
Implementation of a global logical clock to enforce consistent time across every operation in a distributed cluster, further improving data integrity and resilience, along with causal consistency guarantees for read-your-own write consistency
Fully-managed MongoDB Atlas database service launched on AWS, providing built-in automation for resource and workload optimization and always-on security, backed by a 99.995% uptime SLA
MongoDB 3.4 with $graphLookup for native graph processing to identify patterns in connected data; the decimal data type for high precision processing of financial and scientific data; and read-only views to filter and mask data
Zoned sharding to localize data within specific regions and 10x faster data rebalancing across elastically-scaled database clusters
MongoDB Connector for Apache Spark providing seamless integration into data science and AI workflows
MongoDB 3.2 with the Encrypted Storage Engine providing native at-rest encryption without the performance or management overhead of separate filesystem encryption; the In-Memory Storage Engine delivering extreme performance and predictable latency; and the $lookup aggregation pipeline stage to join documents from different collections and databases
Higher database resilience with faster failure detection and recovery via the RAFT-based replication consensus protocol
MongoDB 3.0 with the WiredTiger Storage Engine providing document level concurrency control and built-in compression for an order of magnitude more scalability
MongoDB Ops Manager the self-hosted management platform that enables you to deploy, monitor, back up, and scale MongoDB on your own infrastructure with 95% lower operational overhead
50-member replica sets providing global data distribution