DBMS > H2 vs. PostgreSQL vs. RDF4J vs. Teradata

System Properties Comparison H2 vs. PostgreSQL vs. RDF4J vs. Teradata

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Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Widely used open source RDBMS

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

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Relational DBMS

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

RDF store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	7.57
Rank	#47	Overall
	#30	Relational DBMS

Score	644.36
Rank	#4	Overall
	#4	Relational DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	41.47
Rank	#22	Overall
	#15	Relational DBMS

Website

Technical documentation

www.h2database.com/html/main.html

www.postgresql.org/docs

rdf4j.org/documentation

docs.teradata.com

Developer

Thomas Mueller

PostgreSQL Global Development Group

www.postgresql.org/developer

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Teradata

Initial release

2005

1989

1989: Postgres, 1996: PostgreSQL

2004

1984

Current release

2.2.220, July 2023

16.4, August 2024

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

BSD

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

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.

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Implementation language

Java

Server operating systems

All OS with a Java VM

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

Linux
OS X
Unix
Windows

hosted
Linux

Data scheme

yes

RDF Schemas

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.

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

SQL 2016 + extensions

APIs and other access methods

JDBC
ODBC

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

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

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

Supported programming languages

Java

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Java
PHP
Python

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

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

user defined functions

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

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

none

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

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

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

More information provided by the system vendor

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Related products and services

3rd parties

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pgDash: In-Depth PostgreSQL Monitoring.
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Instaclustr: Fully Hosted & Managed PostgreSQL
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We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

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Conferences, events and webinars

more DBMS events

PASS Data Community Summit
Seattle, Washington, 4-8 November 2024

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