DBMS > Atos Standard Common Repository vs. H2GIS vs. RDF4J vs. Tigris

System Properties Comparison Atos Standard Common Repository vs. H2GIS vs. RDF4J vs. Tigris

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Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

Spatial extension of H2

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

A horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure

Primary database model

Document store
Key-value store

Spatial DBMS

RDF store

Document store
Key-value store
Search engine
Time Series DBMS

Secondary database models

Relational DBMS

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

Score	0.00
Rank	#385	Overall
	#7	Spatial DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	0.05
Rank	#359	Overall
	#50	Document stores
	#52	Key-value stores
	#23	Search engines
	#37	Time Series DBMS

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

www.h2gis.org

rdf4j.org

www.tigrisdata.com

Technical documentation

www.h2gis.org/docs/home

rdf4j.org/documentation

www.tigrisdata.com/docs

Developer

Atos Convergence Creators

CNRS

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

Tigris Data, Inc.

Initial release

2016

2013

2004

2022

Current release

1703

License

Commercial or Open Source

commercial

Open Source

LGPL 3.0

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache Version 2.0

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

Java

Server operating systems

Linux

Linux
OS X
Unix
Windows

Linux
macOS
Windows

Data scheme

Schema and schema-less with LDAP views

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

optional

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

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

LDAP

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

CLI Client
gRPC
RESTful HTTP API

Supported programming languages

All languages with LDAP bindings

Java

Java
PHP
Python

Go
Java
JavaScript (Node.js)

Server-side scripts

Stored procedures

yes

based on H2

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

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, using FoundationDB

In-memory capabilities

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

yes

User concepts

Access control

LDAP bind authentication

yes

based on H2

Access rights for users and roles

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