DBMS > CouchDB vs. GridDB vs. H2 vs. MySQL

System Properties Comparison CouchDB vs. GridDB vs. H2 vs. MySQL

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Editorial information provided by DB-Engines

Name

Description

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

Scalable in-memory time series database optimized for IoT and Big Data

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

Widely used open source RDBMS

Primary database model

Document store

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Spatial DBMS

using the Geocouch extension

Key-value store
Relational DBMS

Spatial DBMS

Document store
Spatial DBMS

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

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

Technical documentation

docs.couchdb.org/en/stable

docs.griddb.net

www.h2database.com/html/main.html

dev.mysql.com/doc

Developer

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Toshiba Corporation

Thomas Mueller

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2005

2013

2005

1995

Current release

3.3.3, December 2023

5.1, August 2022

2.2.220, July 2023

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

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

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

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Implementation language

Erlang

C++

Java

C and C++

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Linux

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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

SQL92, SQL-like TQL (Toshiba Query Language)

yes

with proprietary extensions

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

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

Java

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

View functions in JavaScript

Java Stored Procedures and User-Defined Functions

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

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

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

atomic operations within a single document possible

ACID at container level

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

yes, multi-version concurrency control (MVCC)

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

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GitHub trending repository
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.