DBMS > AgensGraph vs. Citus vs. Postgres-XL vs. STSdb vs. VoltDB

System Properties Comparison AgensGraph vs. Citus vs. Postgres-XL vs. STSdb vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store

Document store
Spatial DBMS

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

bitnine.net/agensgraph

www.citusdata.com

www.postgres-xl.org

github.com/STSSoft/STSdb4

www.voltdb.com

Technical documentation

bitnine.net/documentation

docs.citusdata.com

www.postgres-xl.org/documentation

docs.voltdb.com

Developer

Bitnine Global Inc.

STS Soft SC

VoltDB Inc.

Initial release

2016

2010

2014

since 2012, originally named StormDB

2011

2010

Current release

2.1, December 2018

8.1, December 2018

10 R1, October 2018

4.0.8, September 2015

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

AGPL, commercial license also available

Open Source

Mozilla public license

Open Source

GPLv2, commercial license available

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Java, C++

Server operating systems

Linux
OS X
Windows

Linux

Linux
macOS

Windows

Linux
OS X

for development

Data scheme

depending on used data model

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

standard, with numerous extensions

yes

distributed, parallel query execution

yes

only a subset of SQL 99

APIs and other access methods

Cypher Query Language
JDBC

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

.NET Client API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C
Java
JavaScript
Python

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

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

C#
Java

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions

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

user defined functions

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

MVCC

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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