DBMS > IBM Db2 Event Store vs. MariaDB vs. MarkLogic vs. MongoDB vs. Oracle Berkeley DB

System Properties Comparison IBM Db2 Event Store vs. MariaDB vs. MarkLogic vs. MongoDB vs. Oracle Berkeley DB

Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

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.

Operational and transactional Enterprise NoSQL database

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

Widely used in-process key-value store

Primary database model

Event Store
Time Series DBMS

Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Document store

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Secondary database models

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

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

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	93.21
Rank	#13	Overall
	#9	Relational DBMS

Score	5.92
Rank	#58	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#6	Search engines

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Website

www.ibm.com/products/db2-event-store

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

www.marklogic.com

www.mongodb.com

www.oracle.com/database/technologies/related/berkeleydb.html

Technical documentation

www.ibm.com/docs/en/db2-event-store

mariadb.com/kb/en/library

docs.marklogic.com

www.mongodb.com/docs/manual

docs.oracle.com/cd/E17076_05/html/index.html

Developer

IBM

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

The lead developer Monty Widenius is the original author of MySQL

MarkLogic Corp.

MongoDB, Inc

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2017

2009

Fork of MySQL, which was first released in 1995

2001

2009

1994

Current release

2.0

11.3.2, February 2024

11.0, December 2022

6.0.7, June 2023

18.1.40, May 2020

License

Commercial or Open Source

commercial

free developer edition available

Open Source

GPL version 2, commercial enterprise subscription available

commercial

restricted free version is 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

commercial license available

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.

STACKIT MariaDB offers MariaDB in a fully managed version in enterprise grade, 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.
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.

Implementation language

C and C++

C++

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

yes

Dynamic columns are supported

schema-free

Schema can be enforced

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.

schema-free

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.

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

with proprietary extensions

yes

SQL92

Read-only SQL queries via the MongoDB Atlas SQL Interface

yes

SQL interfaced based on SQLite is available

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Supported programming languages

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

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

C
C#
C++
Java
JavaScript (Node.js)
Perl
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

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Server-side scripts

Stored procedures

yes

PL/SQL compatibility added with version 10.3

yes

via XQuery or JavaScript

JavaScript

Triggers

yes

in MongoDB Atlas only

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Active-active shard replication

Multi-source replication
Source-replica replication

yes

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

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

can act as a resource manager in an XA/JTA transaction

Multi-document ACID Transactions with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

No - written data is immutable

yes

Durability

Support for making data persistent

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

with MEMORY storage engine

yes, with Range Indexes

yes

In-memory storage engine introduced with MongoDB version 3.2

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Role-based access control at the document and subdocument levels

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

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

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

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

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

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

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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