DBMS > CouchDB vs. FatDB vs. H2GIS vs. Kyligence Enterprise vs. PostgreSQL

System Properties Comparison CouchDB vs. FatDB vs. H2GIS vs. Kyligence Enterprise vs. PostgreSQL

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

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

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Spatial extension of H2

A distributed analytics engine for big data, built on top of Apache Kylin

Widely used open source RDBMS

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

Primary database model

Document store

Document store
Key-value store

Spatial DBMS

Relational DBMS

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

Secondary database models

Spatial DBMS

using the Geocouch extension

Relational 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	8.30
Rank	#47	Overall
	#7	Document stores

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Score	0.46
Rank	#266	Overall
	#124	Relational DBMS

Score	636.25
Rank	#4	Overall
	#4	Relational DBMS

Website

couchdb.apache.org

www.h2gis.org

kyligence.io/kyligence-enterprise

www.postgresql.org

Technical documentation

docs.couchdb.org/en/stable

www.h2gis.org/docs/home

www.postgresql.org/docs

Developer

Apache Software Foundation

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

FatCloud

CNRS

Kyligence, Inc.

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

2005

2012

2013

2016

1989

1989: Postgres, 1996: PostgreSQL

Current release

3.3.3, December 2023

16.3, May 2024

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

LGPL 3.0

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

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Implementation language

Erlang

Java

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Windows

Linux

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

Data scheme

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

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

Secondary indexes

yes

via views

yes

SQL

Support of SQL

Via inetgration in SQL Server

yes

ANSI SQL for queries (using Apache Calcite)

yes

standard with numerous extensions

APIs and other access methods

RESTful HTTP/JSON API

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

JDBC
ODBC
RESTful HTTP API

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

Supported programming languages

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

Java

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

View functions in JavaScript

yes

via applications

yes

based on H2

user defined functions

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

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

none

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

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

yes

based on H2

Source-replica replication

other methods possible by using 3rd party extensions

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a single document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

yes, multi-version concurrency control (MVCC)

yes

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

Can implement custom security layer via applications

yes

based on H2

fine grained access rights according to SQL-standard

More information provided by the system vendor

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