DBMS > PostgreSQL vs. SQLite vs. Stardog vs. VoltDB

System Properties Comparison PostgreSQL vs. SQLite vs. Stardog vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

Widely used open source RDBMS

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

Widely used embeddable, in-process RDBMS

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

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

Relational DBMS

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

Relational DBMS

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	645.54
Rank	#4	Overall
	#4	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

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

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

Technical documentation

www.postgresql.org/docs

www.sqlite.org/docs.html

docs.stardog.com

docs.voltdb.com

Developer

PostgreSQL Global Development Group

www.postgresql.org/developer

Dwayne Richard Hipp

Stardog-Union

VoltDB Inc.

Initial release

1989

1989: Postgres, 1996: PostgreSQL

2000

2010

Current release

16.3, May 2024

3.45.3 (15 April 2024), April 2024

7.3.0, May 2020

11.3, April 2022

License

Commercial or Open Source

Open Source

BSD

Open Source

Public Domain

commercial

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

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

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Implementation language

Java

Java, C++

Server operating systems

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

server-less

Linux
macOS
Windows

Linux
OS X

for development

Data scheme

yes

dynamic column types

schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

yes

standard with numerous extensions

yes

SQL-92 is not fully supported

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

yes

only a subset of SQL 99

APIs and other access methods

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

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

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

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

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

user defined functions and aggregates, HTTP Server extensions in Java

Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

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

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 in HA-Cluster

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

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

Users and roles with access to stored procedures

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

3rd parties

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pgDash: In-Depth PostgreSQL Monitoring.
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Redgate webinars: A series of key topics for new PostgreSQL users.
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We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

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Webinar, 10-11am CT / 4-5pm BST, 22 May 2024

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