DBMS > EJDB vs. IBM Db2 vs. Microsoft Azure Cosmos DB vs. MySQL

System Properties Comparison EJDB vs. IBM Db2 vs. Microsoft Azure Cosmos DB vs. MySQL

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Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Common in IBM host environments, 2 different versions for host and Windows/Linux

Globally distributed, horizontally scalable, multi-model database service

Widely used open source RDBMS

Primary database model

Document store

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Spatial DBMS

Document store
Spatial DBMS

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

Score	0.13
Rank	#331	Overall
	#46	Document stores

Score	123.05
Rank	#9	Overall
	#6	Relational DBMS

Score	24.97
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Website

github.com/Softmotions/ejdb

www.ibm.com/products/db2

azure.microsoft.com/services/cosmos-db

www.mysql.com

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

www.ibm.com/docs/en/db2

learn.microsoft.com/azure/cosmos-db

dev.mysql.com/doc

Developer

Softmotions

IBM

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2012

1983

host version

2014

1995

Current release

12.1, October 2016

9.0.0, July 2024

License

Commercial or Open Source

Open Source

GPLv2

commercial

free version is available

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C and C++

Server operating systems

server-less

AIX
HP-UX
Linux
Solaris
Windows
z/OS

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

JSON types

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

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

in-process shared library

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

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

Server-side scripts

Stored procedures

yes

JavaScript

yes

proprietary syntax

Triggers

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

only with Windows/Unix/Linux Version

Sharding

Implicit feature of the cloud service

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

with separate tools (MQ, InfoSphere)

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

Users with fine-grained authorization concept

no user groups or roles

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