DBMS > AgensGraph vs. Datomic vs. Memgraph vs. Microsoft Azure Table Storage vs. MongoDB

System Properties Comparison AgensGraph vs. Datomic vs. Memgraph vs. Microsoft Azure Table Storage vs. MongoDB

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

An open source graph database built for real-time streaming and compatible with Neo4j

A Wide Column Store for rapid development using massive semi-structured datasets

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

Graph DBMS
Relational DBMS

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

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	3.19
Rank	#94	Overall
	#8	Graph DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	421.08
Rank	#5	Overall
	#1	Document stores

Website

bitnine.net/agensgraph

www.datomic.com

memgraph.com

azure.microsoft.com/en-us/services/storage/tables

www.mongodb.com

Technical documentation

bitnine.net/documentation

docs.datomic.com

memgraph.com/docs

www.mongodb.com/docs/manual

Social network pages

Developer

Bitnine Global Inc.

Cognitect

Memgraph Ltd

Microsoft

MongoDB, Inc

Initial release

2016

2012

2017

2012

2009

Current release

2.1, December 2018

1.0.7075, December 2023

6.0.7, June 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

limited edition free

Open Source

BSL 1.1; commercial license for enterprise edition available

commercial

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

yes

MongoDB available as DBaaS (MongoDB Atlas)

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Implementation language

Java, Clojure

C and C++

C++

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Linux

hosted

Linux
OS X
Solaris
Windows

Data scheme

depending on used data model

yes

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.

Typing

predefined data types such as float or date

yes

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

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.

Secondary indexes

yes

SQL

Support of SQL

yes

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

Cypher Query Language
JDBC

RESTful HTTP API

Bolt protocol
Cypher query language

RESTful HTTP API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Supported programming languages

C
Java
JavaScript
Python

Clojure
Java

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

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

yes

Transaction Functions

JavaScript

Triggers

By using transaction functions

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

none

But extensive use of caching in the application peers

Sharding

dynamic graph partitioning

Sharding

Implicit feature of the cloud service

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

Source-replica replication

none

But extensive use of caching in the application peers

Multi-source replication using RAFT

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

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

Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Foreign keys

Referential integrity

yes

relationships in graphs

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

ACID

with snapshot isolation

optimistic locking

Multi-document ACID Transactions with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

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

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

recommended only for testing and development

yes

In-memory storage engine introduced with MongoDB version 3.2

User concepts

Access control

fine grained access rights according to SQL-standard

Users, roles and permissions

Access rights based on private key authentication or shared access signatures

Access rights for users and roles

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...
» more

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...
» more

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,...
» more

Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
» more

Licensing and pricing models

You can check out our pricing model and licenses on the company website .
» more

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.