Editorial information provided by DB-Engines |
Name |
Description | One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure |
Primary database model | Document store |
Secondary database models | Spatial DBMS Search engine integrated Lucene index, currently in MongoDB Atlas only. Time Series DBMS Time Series Collections introduced in Release 5.0 Vector DBMS currently available in the MongoDB Atlas cloud service only |
| |
Website | www.mongodb.com |
Technical documentation | www.mongodb.com/docs/manual |
Developer | MongoDB, Inc |
Initial release | 2009 |
Current release | 7.0.5, January 2024 |
License Commercial or Open Source | Open Source MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available. |
Cloud-based only Only available as a cloud service | no MongoDB available as DBaaS (MongoDB Atlas) |
DBaaS offerings (sponsored links) Database as a Service
Providers of DBaaS offerings, please contact us to be listed. | - MongoDB Flex @ STACKIT offers managed MongoDB Instances with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.
- MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more.
|
Implementation language | C++ |
Server operating systems | Linux OS X Solaris Windows |
Data scheme | schema-free Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema. |
Typing predefined data types such as float or date | yes string, integer, double, decimal, boolean, date, object_id, geospatial |
Secondary indexes | yes |
SQL Support of SQL | Read-only SQL queries via the MongoDB Atlas SQL Interface |
APIs and other access methods | GraphQL HTTP REST Prisma proprietary protocol using JSON |
Supported programming languages | Actionscript unofficial driver C C# C++ Clojure unofficial driver ColdFusion unofficial driver D unofficial driver Dart unofficial driver Delphi unofficial driver Erlang Go Groovy unofficial driver Haskell Java JavaScript Kotlin Lisp unofficial driver Lua unofficial driver MatLab unofficial driver Perl PHP PowerShell unofficial driver Prolog unofficial driver Python R unofficial driver Ruby Rust Scala Smalltalk unofficial driver Swift |
Server-side scripts Stored procedures | JavaScript |
Triggers | yes in MongoDB Atlas only |
Partitioning methods Methods for storing different data on different nodes | Sharding Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime. |
Replication methods Methods for redundantly storing data on multiple nodes | Multi-Source deployments with MongoDB Atlas Global Clusters Source-replica replication |
MapReduce Offers an API for user-defined Map/Reduce methods | yes |
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency can be individually decided for each read operation Immediate Consistency default behaviour |
Foreign keys Referential integrity | no typically not used, however similar functionality with DBRef possible |
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | Multi-document ACID Transactions with snapshot isolation |
Concurrency Support for concurrent manipulation of data | yes |
Durability Support for making data persistent | yes optional, enabled by default |
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes In-memory storage engine introduced with MongoDB version 3.2 |
User concepts Access control | Access rights for users and roles |
More information provided by the system vendor |
|
Specific characteristics | MongoDB provides an integrated suite of cloud database and data services to accelerate and simplify how developers build with data. MongoDB has been one of the fastest growing databases over the past decade in DB-Engines Rankings, and is consistently rated as one of the databases developers most want to use in Stack Overflow's annual developer survey. Developers love working with MongoDB because they: - Develop faster with the document model: MongoDB's JSON-like document data model maps to the objects in your application code. Its flexibility allows you to model data of any structure – from the vast diversity of regular application data to vector embeddings composed of several thousand dimensions. Any of these structures can be modified at any time.
Work with data as code for any use case. MongoDB's unified query API is the most natural way to work with data in any form. Atlas extends MongoDB's flexibility and ease of use to building AI-enriched apps with in-app intelligence, semantic and keyword search, time-series and geospatial applications, and streaming, event-driven services. Perform securely at any scale. MongoDB's distributed systems foundation means you cn scale-out your database on-demand, with full redundancy and built-in, always-on security controls
|
Competitive advantages | Built around the flexible document data model and unified API, MongoDB is a developer data platform, designed to work with data any way your application needs. Working with data in-motion and data at-rest, MongoDB Atlas provides all of the core data services that enable developers to build any class of modern, intelligent software. MongoDB has been named a leader in 2022 Gartner® Magic Quadrant™ for Cloud Database Management Systems, and as a leader in the Forrester WaveTM: Translytical Data Platforms, Q4 2022 MongoDB University offers no cost training for developers and operations teams for all of MongoDB's products Atlas Database: A transactional multi-cloud database service built for operational applications demanding the highest levels of resilience, scale, data privacy, and security. Atlas Vector Search: Build intelligent applications powered by semantic search and generative AI over any type of data.
Atlas Search: Build fast, relevance-based keyword search directly into an app without the need for a bolt-on search engine. - Atlas Stream Processing: Easily create applications that leverage streaming data. Developers can continuously process and analyze streams of complex data using the same MongoDB drivers, query API, and flexible data model they use for the database.
Atlas Charts: Bring your data to life and get real-time insights with embeddable dashboards and visualizations. Atlas Data Lake: A fully managed storage solution that provides the economics of cloud object storage and is optimized for analytical queries Atlas Data Federation: Seamlessly query, transform, and aggregate data from one or more Atlas databases and cloud object storage offerings Atlas Online Archive: Tier aged data from Atlas databases to fully managed object storage and query it through a single endpoint. Atlas App Services: APIs, Triggers, Functions to build apps, integrate services, and connect to your data without operational overhead. Atlas Device Sync: Keep your data up-to-date across devices, users, and your backend
|
Typical application scenarios | AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of Things and Time Series (Bosch, GE Healthcare, Jaguar Land Rover) Mobile (Cathay Pacific, Telefonica, ADP) eCommerce (Cisco, 7-Eleven) Single View (MetLife, AO.com) Personalization (Glassdoor, Expedia, eHarmony) Catalogs (Under Armour, Keller Williams, Forbes) Gaming (EA, Epic Games, Sega) Payments (Coinbase, Nets Group, Macquarie Group) Mainframe Offload (Alight Solutions, Barclays, Nationwide)
|
Key customers | ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN, City of Chicago, Coinbase, Department of Veteran Affairs, Department of Works and Pensions, eBay, eHarmony, Electronic Arts, Elsevier, Epic Games, Expedia, Forbes, Foursquare, Gap, Genentech, HSBC, Jaguar Land Rover, KPMG, MetLife, Morgan Stanley, Nationwide, Nat West, OTTO, Pearson, Porsche, RBS, Sage, Salesforce, SAP, Sega, Sprinklr, Telefonica, The Weather Channel, Ticketmaster, Under Armour, Verizon Wireless, Vodafone, Volvo See more MongoDB customers. |
Market metrics | Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month handling tens of PBs of data, and serving hundreds of billions of queries every day. MongoDB Atlas is available in 110+ cloud regions across AWS, Azure, and Google Cloud
43,000+ customers in more than 100 countries around the world. Includes more than 50% of the Fortune 100 Named a leader in 2022 Gartner® Magic Quadrant™ for Cloud Database Management Systems, and as a leader in the Forrester WaveTM: Translytical Data Platforms, Q4 2022 1.5M+ registrations for MongoDB University courses More than 1,000 technology and service partners Highest placed non-relational database in DB Engines rankings
|
Licensing and pricing models | |
Related products and servicesWe invite representatives of vendors of related products to contact us for presenting information about their offerings here. |
More resources |
|
DB-Engines blog posts | Snowflake is the DBMS of the Year 2021 3 January 2022, Paul Andlinger, Matthias Gelbmann PostgreSQL is the DBMS of the Year 2020 4 January 2021, Paul Andlinger, Matthias Gelbmann PostgreSQL is the DBMS of the Year 2018 2 January 2019, Paul Andlinger, Matthias Gelbmann show all |
Recent citations in the news | TencentDB, MongoDB Renew Strategic Partnership for AI Data Management 23 April 2025, The Fast Mode MongoDB (MDB) Rises Yet Lags Behind Market: Some Facts Worth Knowing 22 April 2025, Yahoo MongoDB CFO to step down, successor search underway 21 April 2025, Investing.com Why MongoDB Stock Lost 34% in March 8 April 2025, The Motley Fool Market Whales and Their Recent Bets on MDB Options 24 April 2025, Benzinga provided by Google News |