DBMS > MongoDB
MongoDB System Properties
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|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||Search engine integrated Lucene index, currently in MongoDB Atlas only.|
|Current release||4.4.2, November 2020|
|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 inofficial driver|
Clojure inofficial driver
ColdFusion inofficial driver
D inofficial driver
Dart inofficial driver
Delphi inofficial driver
Groovy inofficial driver
Lisp inofficial driver
Lua inofficial driver
MatLab inofficial driver
PowerShell inofficial driver
Prolog inofficial driver
R inofficial driver
Smalltalk inofficial 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|
|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|
|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 is the leading modern, general purpose data platform, designed to unleash the power of software and data for developers and the applications they build. The world's most sophisticated organizations, from cutting-edge startups to the largest companies and government agencies, use MongoDB to create applications never before possible, at a fraction of the cost of legacy databases.
In 2020, MongoDB was named as the database developers most wanted to use in the Stack Overflow Developer survey. 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 and MongoDB Query Language, giving developers the fastest way to innovate in building transactional, operational and analytical applications.
MongoDB offers the fully managed, on-demand and global MongoDB Atlas service in the public cloud. Atlas enables customers to take advantage of MongoDB’s capabilities on AWS, Azure, or GCP without needing to deploy, operate, and scale the software or underlying infrastructure themselves.
MongoDB Cloud extends Atlas with other data services that work with it seamlessly, giving you more ways of working with data.
MongoDB Atlas Search makes it easy to create fast, relevant, full-text search capabilities on top of your data in the cloud, and is built on top of Apache Lucene, the industry standard library.
The service is fully managed, operationally invisible, and integrated within the Atlas cloud database, removing the need for teams to deploy and manage a separate search platform. Search functionality is also exposed via the MongoDB query language so developers do not need to learn a new API. Simply create search indexes directly in Atlas and use the MongoDB query language to build sophisticated search queries.
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 Language (MQL).
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 extends your data foundation out to the edge of the network, and is fully integrated with the MongoDB Cloud. Realm is a lightweight database embedded directly on the client device. Realm helps solve the unique challenges of building for mobile, making it simple to store data on-device and enabling data access even when offline.
MongoDB Realm Sync is seamlessly integrated and keeps data up-to-date across devices and users by automatically, bi-directionally syncing data between the client and a backend Atlas database cluster.
MongoDB Realm Application Services go further, simplifying the code required to stand up both mobile and web applications. Realm’s SDKs give developers the tools needed to access data stored in MongoDB Atlas directly from the client, and interact with the platform’s application services.
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 Cloud 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.
MongoDB Cloud 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 Cloud 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|
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|Studio 3T: The world's favorite IDE for working with MongoDB|
|Navicat for MongoDB gives you a highly effective GUI interface for MongoDB database management, administration and development.|
|CData: Connect to Big Data & NoSQL through standard Drivers.|
We invite representatives of vendors of related products to contact us for presenting information about their offerings here.
|DB-Engines blog posts|
PostgreSQL is the DBMS of the Year 2018 PostgreSQL moves up one rank at the expense of MongoDB Oracle is the DBMS of the Year Manager, NTSE Americas — MongoDB MongoDB Atlas Online Archive brings data tiering to DBaaS Why MongoDB, DocuSign, and Fastly Stocks Tanked on Tuesday Analysts Estimate MongoDB (MDB) to Report a Decline in Earnings: What to Look Out for Developers increasingly pair MongoDB with PostgreSQL, survey finds provided by Google News Entry-Level Programmer, 100% Remote Software Engineer Internship Jr. QA Analyst Trainee MongoDB Software Engineer II
PostgreSQL moves up one rank at the expense of MongoDB Oracle is the DBMS of the Year Manager, NTSE Americas — MongoDB MongoDB Atlas Online Archive brings data tiering to DBaaS Why MongoDB, DocuSign, and Fastly Stocks Tanked on Tuesday Analysts Estimate MongoDB (MDB) to Report a Decline in Earnings: What to Look Out for Developers increasingly pair MongoDB with PostgreSQL, survey finds provided by Google News Entry-Level Programmer, 100% Remote Software Engineer Internship Jr. QA Analyst Trainee MongoDB Software Engineer II
Oracle is the DBMS of the Year Manager, NTSE Americas — MongoDB MongoDB Atlas Online Archive brings data tiering to DBaaS Why MongoDB, DocuSign, and Fastly Stocks Tanked on Tuesday Analysts Estimate MongoDB (MDB) to Report a Decline in Earnings: What to Look Out for Developers increasingly pair MongoDB with PostgreSQL, survey finds provided by Google News Entry-Level Programmer, 100% Remote Software Engineer Internship Jr. QA Analyst Trainee MongoDB Software Engineer II
Manager, NTSE Americas — MongoDB
MongoDB Atlas Online Archive brings data tiering to DBaaS
Why MongoDB, DocuSign, and Fastly Stocks Tanked on Tuesday
Developers increasingly pair MongoDB with PostgreSQL, survey finds
provided by Google News
Entry-Level Programmer, 100% Remote
Software Engineer Internship
Jr. QA Analyst Trainee
Software Engineer II
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