DBMS > Citus vs. CouchDB vs. PouchDB vs. Snowflake vs. TerarkDB

System Properties Comparison Citus vs. CouchDB vs. PouchDB vs. Snowflake vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

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

JavaScript DBMS with an API inspired by CouchDB

Cloud-based data warehousing service for structured and semi-structured data

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Secondary database models

Document store

Spatial DBMS

using the Geocouch extension

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

Score	2.15
Rank	#117	Overall
	#56	Relational DBMS

Score	8.30
Rank	#47	Overall
	#7	Document stores

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Website

github.com/bytedance/terarkdb

Technical documentation

docs.citusdata.com

docs.couchdb.org/en/stable

pouchdb.com/guides

docs.snowflake.net/manuals/index.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Apache Software Foundation

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

Apache Software Foundation

Snowflake Computing Inc.

ByteDance, originally Terark

Initial release

2010

2005

2012

2014

2016

Current release

8.1, December 2018

3.3.3, December 2023

7.1.1, June 2019

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

Open Source

Apache version 2

Open Source

commercial

restricted open source version available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

JavaScript

C++

Server operating systems

Linux

Android
BSD
Linux
OS X
Solaris
Windows

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

hosted

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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

yes

Secondary indexes

yes

via views

yes

via views

SQL

Support of SQL

yes

standard, with numerous extensions

yes

APIs and other access methods

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

RESTful HTTP/JSON API

HTTP REST

only for PouchDB Server
JavaScript API

CLI Client
JDBC
ODBC

C++ API
Java API

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

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

JavaScript

JavaScript (Node.js)
Python

C++
Java

Server-side scripts

Stored procedures

user defined functions

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

View functions in JavaScript

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

with a proxy-based framework, named couchdb-lounge

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

Multi-source replication
Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes

none

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a single document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

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

Access rights for users can be defined per database

Users with fine-grained authorization concept, user roles and pluggable authentication

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