DBMS > H2 vs. MySQL vs. OrientDB vs. PouchDB vs. Trafodion

System Properties Comparison H2 vs. MySQL vs. OrientDB vs. PouchDB vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Widely used open source RDBMS

Multi-model DBMS (Document, Graph, Key/Value)

JavaScript DBMS with an API inspired by CouchDB

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

Key/Value like access via memcached API

Document store
Graph DBMS
Key-value store

Document store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Score	2.34
Rank	#112	Overall
	#21	Document stores

Website

Technical documentation

www.h2database.com/html/main.html

dev.mysql.com/doc

www.orientdb.com/docs/last/index.html

pouchdb.com/guides

trafodion.apache.org/documentation.html

Developer

Thomas Mueller

Oracle

since 2010, originally MySQL AB, then Sun

OrientDB LTD; CallidusCloud; SAP

Apache Software Foundation

Apache Software Foundation, originally developed by HP

Initial release

2005

1995

2010

2012

2014

Current release

2.2.220, July 2023

8.4.0, April 2024

3.2.29, March 2024

7.1.1, June 2019

2.3.0, February 2019

License

Commercial or Open Source

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache version 2

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

Java

JavaScript

C++, Java

Server operating systems

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

All OS with a Java JDK (>= JDK 6)

server-less, requires a JavaScript environment (browser, Node.js)

Linux

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

schema-free

yes

Typing

predefined data types such as float or date

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

via views

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language, no joins

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

HTTP REST

only for PouchDB Server
JavaScript API

ADO.NET
JDBC
ODBC

Supported programming languages

Java

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

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

JavaScript

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

yes

proprietary syntax

Java, Javascript

View functions in JavaScript

Java Stored Procedures

Triggers

yes

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

Multi-source replication
Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

relationship in graphs

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and roles; record level security configurable

fine grained access rights according to SQL-standard

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