DBMS > EsgynDB vs. Fujitsu Enterprise Postgres vs. RDF4J vs. SpatiaLite

System Properties Comparison EsgynDB vs. Fujitsu Enterprise Postgres vs. RDF4J vs. SpatiaLite

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Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

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

Spatial extension of SQLite

Primary database model

Relational DBMS

RDF store

Spatial DBMS

Secondary database models

Document store
Spatial DBMS

Relational DBMS

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.37
Rank	#278	Overall
	#128	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	1.63
Rank	#146	Overall
	#3	Spatial DBMS

Website

www.esgyn.cn

www.postgresql.fastware.com

rdf4j.org

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

www.postgresql.fastware.com/product-manuals

rdf4j.org/documentation

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Esgyn

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

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

Alessandro Furieri

Initial release

2015

2004

2008

Current release

Fujitsu Enterprise Postgres 14, January 2022

5.0.0, August 2020

License

Commercial or Open Source

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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

Java

C++

Server operating systems

Linux

Linux
Windows

Linux
OS X
Unix
Windows

server-less

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
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

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

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

Java
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

partitioning by range, list and by hash

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

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

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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