DBMS > Citus vs. PouchDB vs. Stardog vs. SWC-DB

System Properties Comparison Citus vs. PouchDB vs. Stardog vs. SWC-DB

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Editorial information provided by DB-Engines

Name

Description

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

JavaScript DBMS with an API inspired by CouchDB

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

A high performance, scalable Wide Column DBMS

Primary database model

Secondary database models

Document store

Time Series DBMS

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

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

www.citusdata.com

pouchdb.com

www.stardog.com

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.citusdata.com

pouchdb.com/guides

docs.stardog.com

Developer

Apache Software Foundation

Stardog-Union

Alex Kashirin

Initial release

2010

2012

2010

2020

Current release

8.1, December 2018

7.1.1, June 2019

7.3.0, May 2020

0.5, April 2021

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

Open Source

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

Java

C++

Server operating systems

Linux

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

Linux
macOS
Windows

Linux

Data scheme

yes

schema-free

schema-free and OWL/RDFS-schema support

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

Import/export of XML data possible

Secondary indexes

yes

via views

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

standard, with numerous extensions

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

SQL-like query language

APIs and other access methods

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

HTTP REST

only for PouchDB Server
JavaScript API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Proprietary protocol
Thrift

Supported programming languages

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

JavaScript

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C++

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 and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

with a proxy-based framework, named couchdb-lounge

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication in HA-Cluster

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 in HA-Cluster

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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 and roles

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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