DBMS > MongoDB
MongoDB System Properties
Please select another system to compare it with MongoDB.
|Editorial information provided by DB-Engines|
|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
|Current release||5.0.5, December 2021|
|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.
|Server operating systems||Linux|
|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|
|SQL Support of SQL||Read-only SQL queries via the MongoDB Connector for BI|
|APIs and other access methods||proprietary protocol using JSON|
|Supported programming languages||Actionscript unofficial driver|
Clojure unofficial driver
ColdFusion unofficial driver
D unofficial driver
Dart unofficial driver
Delphi unofficial driver
Groovy unofficial driver
Lisp unofficial driver
Lua unofficial driver
MatLab unofficial driver
PowerShell unofficial driver
Prolog unofficial driver
R unofficial driver
Smalltalk unofficial driver
|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|
|MapReduce Offers an API for user-defined Map/Reduce methods||yes|
|Consistency concepts Methods to ensure consistency in a distributed system||Eventual Consistency|
Immediate Consistency can be individually decided for each write operation
|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|
MongoDB’s application data platform provides developers a unified interface to power operational and transactional database requirements plus search, real-time and data lake applications needs. This enables developers to move fast and simplify how they build with data for almost any class of application.
In its most recent developer survey, Stack Overflow names MongoDB as the database developers most wanted to use. This was the 4th consequetive year MongoDB had topped this poll. MongoDB was also named a leader in the Forrester Wave™: Big Data NoSQL, Q1 2019 and in the Forrester Wave: Database-As-A-Service, Q2 2019
MongoDB is designed to meet the demands of modern apps with a technology foundation that enables you through:
1. The document data model, giving developers the easiest and most intuitive way to work with data.
2. The MongoDB Query API, giving developers the fastest way to innovate in building transactional, operational and analytical applications.
3. Delivered as a multi-cloud, global platform, giving developers the freedom to run their applications anywhere with the flexibility to move data across private and public clouds as requirements evolve – without having to change a single line of code. Atlas enables customers to take advantage of MongoDB’s capabilities across AWS, Azure, and GCP without needing to deploy, operate, and scale the software or underlying infrastructure themselves.
All of this comes together as the MongoDB Application Data Platform, providing a unified developer experience for modern applications that span cloud to edge.
MongoDB Atlas Search exposes a fully-managed Apache Lucene index directly on top of the MongoDB database, enabling developers to create rich, relevance-based search experiences without having to move their data into a separate search engine. Atlas Search offers advanced full-text search features including auto-complete, typo tolerance, function scoring, and synonyms – all fully integrated into the MongoDB API so developers don’t need to context switch to another query language.
MongoDB Atlas Data Lake brings a serverless, scalable data lake to the cloud platform with an on-demand query service that enables you to analyze data in cloud object storage (Amazon S3) in-place using the MongoDB Query API.
There is no infrastructure to set up or manage and no need to capacity plan as Atlas Data Lake automatically parallelizes operations by breaking queries down and then dividing the work across multiple compute nodes. Support for federated queries allows you to combine and analyze data across S3 and your Atlas database clusters together with a single query. In addition, you can easily persist the results of your aggregations to either object storage or your cloud database. Supported data formats include JSON, BSON, CSV, TSV, Avro, ORC and Parquet.
Atlas Data Lake is also the technology underpinning the Atlas Online Archive, which allows you to automatically move historical data out of your database to cloud object storage while retaining query access through the same connection string.
The MongoDB Realm Mobile Database allows developers to store data locally on iOS and Android devices using a rich data model that’s intuitive to them. Combined with the MongoDB Realm sync-to-Atlas, Realm makes it simple to build reactive, reliable apps that work even when users are offline.
MongoDB Realm Application Services allow developers to validate and build key features quickly. Application development services like Realm Sync for mobile and Realm’s GraphQL service, can be used with Realm Functions, Triggers, and Data Access Rules – all simplifying the code required to build secure and performant apps.
All of the components of MongoDB’s application data platform are designed to accelerate developer productivity and eliminate the tax on innovation that comes with sprawling data infrastructures. We believe it provides the best approach with a unified interface that can support any type of application workload, without limiting you to a single deployment environment.
The MongoDB platform can be used by developers building transactional, operational, and analytical apps. Through its design, MongoDB provides a technology foundation to meet the demands of modern apps, enabling developers to work with data wherever it lives: on device, in the application’s backend database and search engine, and in the data lake.
MongoDB maintains the most valuable features of relational databases: strong consistency, ACID transactions, expressive query language and secondary indexes. As a result, developers can build highly functional applications faster than NoSQL databases.
MongoDB provides the data model flexibility, elastic scalability, along with the performance and resilience of NoSQL databases. As a result, developers can continuously enhance applications, and deliver them at almost unlimited scale wherever they choose to run them.
Across all of the services in the MongoDB Cloud, developers benefit from a consistent and elegant developer experience. From database to search to analytics on your data lake, there’s a common way of working with data that simplifies development. Unlike other cloud data platforms that require you to learn entirely different technologies and APIs, MongoDB Cloud presents all its services in a single system and with a consistent interface.
MongoDB runs on multi-cloud infrastructure. You can choose underlying infra from AWS, GCP, or Azure and get a consistent experience, deploying and controlling clusters in different clouds from a single UI. Avoid lock-in or take advantage of different cloud vendor’s services with simple data portability across clouds.
The MongoDB application data platform is fully managed for operational simplicity. From the basics of deployment automation and monitoring to advanced features like auto-scale and intelligent performance advice, MongoDB gets operations out of your way. Clusters are fully managed, data synchronization between services is automated, and making adjustments is as easy as a button click or API call.
MongoDB Cloud works with your ecosystem. Manage your infrastructure as code with Kubernetes and Terraform integrations, plug in your monitoring and alerting tools, integrate with your security environment, connect to data tools like Kafka and Spark, and work with MongoDB integrations in your usual IDEs.
|Typical application scenarios|
Review the MongoDB Use Case Guidance whitepaper to learn more about those use cases served by the MongoDB Data Platform, and where you should evaluate alternative solutions.
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, OTTO, Pearson, Porsche, RBS, Sage, Salesforce, SAP, Sega, Sprinklr, Telefonica, The Weather Channel, Ticketmaster, Under Armour, Verizon Wireless
See more MongoDB customers.
|Licensing and pricing models|
|Related products and services|
|Studio 3T: The world's favorite IDE for working with MongoDB|
|CData: Connect to Big Data & NoSQL through standard Drivers.|
|Fivetran: Quickly and easily centralize your on-premise and cloud databases.|
|Navicat for MongoDB gives you a highly effective GUI interface for MongoDB database management, administration and development.|
We invite representatives of vendors of related products to contact us for presenting information about their offerings here.
|DB-Engines blog posts|
Snowflake is the DBMS of the Year 2021 PostgreSQL is the DBMS of the Year 2020 PostgreSQL is the DBMS of the Year 2018 MongoDB 5.2 database improves time series capabilities MongoDB's Mark Porter on Database Trends and the 'Innovation Tax' | eWEEK Is MongoDB, Inc. (NASDAQ:MDB) Expensive For A Reason? A Look At Its Intrinsic Value Does MongoDB (NASDAQ:MDB) Have A Healthy Balance Sheet? Leaving Shared Database Accounts Behind: Securing Snowflake and MongoDB provided by Google News Front-end Web Developer MongoDB Cloud Support Engineer I - Databases CW Front End Developer Junior MongoDB NoSQL Database Engineer
PostgreSQL is the DBMS of the Year 2020 PostgreSQL is the DBMS of the Year 2018 MongoDB 5.2 database improves time series capabilities MongoDB's Mark Porter on Database Trends and the 'Innovation Tax' | eWEEK Is MongoDB, Inc. (NASDAQ:MDB) Expensive For A Reason? A Look At Its Intrinsic Value Does MongoDB (NASDAQ:MDB) Have A Healthy Balance Sheet? Leaving Shared Database Accounts Behind: Securing Snowflake and MongoDB provided by Google News Front-end Web Developer MongoDB Cloud Support Engineer I - Databases CW Front End Developer Junior MongoDB NoSQL Database Engineer
PostgreSQL is the DBMS of the Year 2018 MongoDB 5.2 database improves time series capabilities MongoDB's Mark Porter on Database Trends and the 'Innovation Tax' | eWEEK Is MongoDB, Inc. (NASDAQ:MDB) Expensive For A Reason? A Look At Its Intrinsic Value Does MongoDB (NASDAQ:MDB) Have A Healthy Balance Sheet? Leaving Shared Database Accounts Behind: Securing Snowflake and MongoDB provided by Google News Front-end Web Developer MongoDB Cloud Support Engineer I - Databases CW Front End Developer Junior MongoDB NoSQL Database Engineer
MongoDB 5.2 database improves time series capabilities
MongoDB's Mark Porter on Database Trends and the 'Innovation Tax' | eWEEK
Does MongoDB (NASDAQ:MDB) Have A Healthy Balance Sheet?
provided by Google News
Front-end Web Developer
Cloud Support Engineer I - Databases
CW Front End Developer
Junior MongoDB NoSQL Database Engineer
Share this page