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

Java

C and C++

C++

Java

Server operating systems

All OS with a Java VM

Linux

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

hosted
Linux

Data scheme

schema-free

schema-free and schema-optional

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.

predefined scheme

yes

Typing

predefined data types such as float or date

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

Read-only SQL queries via the MongoDB Atlas SQL Interface

yes

SQL 2016 + extensions

APIs and other access methods

JCache

Bolt protocol
Cypher query language

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

HTTP REST

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

Java

.Net
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala

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

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

JavaScript

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Cache Event Listeners

yes

in MongoDB Atlas only

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding

dynamic graph partitioning

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.

Sharding

based on HBase

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

Multi-source replication using RAFT

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

selectable replication factor

based on HBase

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

yes

supports JTA and can work as an XA resource

ACID

with snapshot isolation

Multi-document ACID Transactions with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

with periodic snapshot and write-ahead logging (WAL) of changes

yes

optional, enabled by default

yes

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

yes

User concepts

Access control

Users, roles and permissions

Access rights for users and roles

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Memgraph directly connects to your streaming infrastructure so you and your team...
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MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

Business Source License ensures a future for the Memgraph community MAGE algorithm...
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Built around the flexible document data model and unified API, MongoDB is a developer...
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Typical application scenarios

Graph algorithms in bioinformatics Social network analysis Cryptocurrency network...
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AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Licensing and pricing models

You can check out our pricing model and licenses on the company website .
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MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.