DBMS > AgensGraph vs. Citus vs. Postgres-XL vs. Teradata vs. ToroDB

System Properties Comparison AgensGraph vs. Citus vs. Postgres-XL vs. Teradata vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

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

A hybrid cloud data analytics software platform (Teradata Vantage)

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

Document store

Secondary database models

Document store

Document store
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series 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	45.33
Rank	#21	Overall
	#15	Relational DBMS

Website

bitnine.net/agensgraph

www.citusdata.com

www.postgres-xl.org

www.teradata.com

github.com/torodb/server

Technical documentation

bitnine.net/documentation

docs.citusdata.com

www.postgres-xl.org/documentation

docs.teradata.com

Developer

Bitnine Global Inc.

Teradata

8Kdata

Initial release

2016

2010

2014

since 2012, originally named StormDB

1984

2016

Current release

2.1, December 2018

8.1, December 2018

10 R1, October 2018

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

AGPL, commercial license also available

Open Source

Mozilla public license

commercial

Open Source

AGPL-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

Java

Server operating systems

Linux
OS X
Windows

Linux

Linux
macOS

hosted
Linux

All OS with a Java 7 VM

Data scheme

depending on used data model

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

yes

Secondary indexes

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

yes

standard, with numerous extensions

yes

distributed, parallel query execution

yes

SQL 2016 + extensions

APIs and other access methods

Cypher Query Language
JDBC

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

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

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
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

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

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

horizontal partitioning

Sharding

Hashing

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
Source-replica 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

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

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

fine grained access rights according to SQL-standard

Access rights for users and roles

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More resources

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