DBMS > H2 vs. PostgreSQL vs. PouchDB vs. Riak KV

System Properties Comparison H2 vs. PostgreSQL vs. PouchDB vs. Riak KV

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Editorial information provided by DB-Engines

Name

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

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

JavaScript DBMS with an API inspired by CouchDB

Distributed, fault tolerant key-value store

Primary database model

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Document store

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Secondary database models

Spatial DBMS

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	636.25
Rank	#4	Overall
	#4	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Website

www.h2database.com

www.postgresql.org

pouchdb.com

Technical documentation

www.h2database.com/html/main.html

www.postgresql.org/docs

pouchdb.com/guides

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Thomas Mueller

PostgreSQL Global Development Group

www.postgresql.org/developer

Apache Software Foundation

OpenSource, formerly Basho Technologies

Initial release

2005

1989

1989: Postgres, 1996: PostgreSQL

2012

2009

Current release

2.2.220, July 2023

16.3, May 2024

7.1.1, June 2019

3.2.0, December 2022

License

Commercial or Open Source

Open Source

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

Open Source

BSD

Open Source

Apache version 2, commercial enterprise edition

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

JavaScript

Erlang

Server operating systems

All OS with a Java VM

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

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

Linux
OS X

Data scheme

yes

schema-free

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

via views

restricted

SQL

Support of SQL

yes

standard with numerous extensions

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP REST

only for PouchDB Server
JavaScript API

HTTP API
Native Erlang Interface

Supported programming languages

Java

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

JavaScript

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

View functions in JavaScript

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

partitioning by range, list and (since PostgreSQL 11) by hash

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

no "single point of failure"

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

Source-replica replication

other methods possible by using 3rd party extensions

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

yes, using Riak Security

More information provided by the system vendor

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