DBMS > FoundationDB vs. H2GIS vs. Oracle Berkeley DB vs. PostGIS vs. RDF4J

System Properties Comparison FoundationDB vs. H2GIS vs. Oracle Berkeley DB vs. PostGIS vs. RDF4J

Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

Description

Ordered key-value store. Core features are complimented by layers.

Spatial extension of H2

Widely used in-process key-value store

Spatial extension of PostgreSQL

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

Primary database model

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Spatial DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Spatial DBMS

RDF store

Secondary database models

Relational DBMS

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

Score	1.03
Rank	#190	Overall
	#31	Document stores
	#28	Key-value stores
	#89	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

github.com/apple/foundationdb

www.h2gis.org

www.oracle.com/database/technologies/related/berkeleydb.html

postgis.net

rdf4j.org

Technical documentation

apple.github.io/foundationdb

www.h2gis.org/docs/home

docs.oracle.com/cd/E17076_05/html/index.html

postgis.net/documentation

rdf4j.org/documentation

Developer

FoundationDB

CNRS

Oracle

originally developed by Sleepycat, which was acquired by Oracle

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

Initial release

2013

1994

2005

2004

Current release

6.2.28, November 2020

18.1.40, May 2020

3.4.2, February 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

LGPL 3.0

Open Source

commercial license available

Open Source

GPL v2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

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

C++

Java

C, Java, C++ (depending on the Berkeley DB edition)

Java

Server operating systems

Linux
OS X
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

some layers support schemas

yes

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

some layers support typing

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

only with the Berkeley DB XML edition

yes

Secondary indexes

yes

SQL

Support of SQL

supported in specific SQL layer only

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

Java

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Java
PHP
Python

Server-side scripts

Stored procedures

in SQL-layer only

yes

based on H2

user defined functions

yes

Triggers

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

based on PostgreSQL

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

Source-replica replication

yes

based on PostgreSQL

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

in SQL-layer only

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

In-memory capabilities

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

yes

User concepts

Access control

yes

based on H2

yes

based on PostgreSQL

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More resources

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