DBMS > Datastax Enterprise vs. Datomic vs. MariaDB vs. MongoDB vs. ObjectBox

System Properties Comparison Datastax Enterprise vs. Datomic vs. MariaDB vs. MongoDB vs. ObjectBox

Editorial information provided by DB-Engines

Name

Description

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

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

MySQL application compatible open source RDBMS, enhanced with high availability, security, interoperability and performance capabilities. MariaDB ColumnStore provides a column-oriented storage engine and MariaDB Xpand supports distributed SQL.

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

Extremely fast embedded database for small devices, IoT and Mobile

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

Document store
Graph DBMS

with OQGraph storage engine
Spatial DBMS

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

Time Series DBMS

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

Score	5.93
Rank	#56	Overall
	#4	Wide column stores

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	91.04
Rank	#13	Overall
	#9	Relational DBMS

Score	421.08
Rank	#5	Overall
	#1	Document stores

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS

Website

www.datastax.com/products/datastax-enterprise

www.datomic.com

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

www.mongodb.com

objectbox.io

Technical documentation

docs.datastax.com

docs.datomic.com

mariadb.com/kb/en/library

www.mongodb.com/docs/manual

docs.objectbox.io

Developer

DataStax

Cognitect

MariaDB Corporation Ab (MariaDB Enterprise),
MariaDB Foundation (community MariaDB Server)

The lead developer Monty Widenius is the original author of MySQL

MongoDB, Inc

ObjectBox Limited

Initial release

2011

2012

2009

Fork of MySQL, which was first released in 1995

2009

2017

Current release

6.8, April 2020

1.0.7075, December 2023

11.3.2, February 2024

6.0.7, June 2023

License

Commercial or Open Source

commercial

limited edition free

Open Source

GPL version 2, commercial enterprise subscription available

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.

STACKIT MariaDB offers MariaDB in a fully managed version in enterprise grade, 100% GDPR-compliant.

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

Java

Java, Clojure

C and C++

C++

C and C++

Server operating systems

Linux
OS X

All OS with a Java VM

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

Linux
OS X
Solaris
Windows

Android
iOS
Linux
macOS
Windows

Data scheme

schema-free

yes

Dynamic columns are supported

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.

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

SQL

Support of SQL

SQL-like DML and DDL statements (CQL); Spark SQL

yes

with proprietary extensions

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Proprietary native API

Supported programming languages

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

Clojure
Java

Ada
C
C#
C++
D
Eiffel
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

PL/SQL compatibility added with version 10.3

JavaScript

Triggers

yes

By using transaction functions

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

none

But extensive use of caching in the application peers

several options for horizontal partitioning and Sharding

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.

none

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware, advanced replication for edge computing

none

But extensive use of caching in the application peers

Multi-source replication
Source-replica replication

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

online/offline synchronization between client and server

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Atomicity and isolation are supported for single operations

ACID

not for MyISAM storage engine

Multi-document ACID Transactions with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

yes

not for in-memory storage engine

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

recommended only for testing and development

yes

with MEMORY storage engine

yes

In-memory storage engine introduced with MongoDB version 3.2

User concepts

Access control

Access rights for users can be defined per object

fine grained access rights according to SQL-standard

Access rights for users and roles

yes

More information provided by the system vendor

Specific characteristics

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
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MariaDB is the most powerful open source relational database – modern SQL and JSON...
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MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
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MariaDB Servers have many features unavailable in other open source relational databases....
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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

Applications that must be massively and linearly scalable with 100% uptime and able...
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Web, SaaS and Cloud operational applications that require high availability, scalability...
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AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
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Deutsche Bank, DBS Bank, Nasdaq, Red Hat, ServiceNow, Verizon and Walgreens Featured...
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ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
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MariaDB is the default database in the LAMP stack supplied by Red Hat and SUSE Linux,...
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Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Licensing and pricing models

Annual subscription
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MariaDB plc subscriptions cover our free, open source database, Community Server,...
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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.