DBMS > Atos Standard Common Repository vs. H2GIS vs. RDF4J vs. Transwarp Hippo

System Properties Comparison Atos Standard Common Repository vs. H2GIS vs. RDF4J vs. Transwarp Hippo

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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.

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Document store
Key-value store

Spatial DBMS

RDF store

Vector DBMS

Secondary database models

Relational DBMS

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

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	0.05
Rank	#386	Overall
	#16	Vector DBMS

Website

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

www.h2gis.org

rdf4j.org

www.transwarp.cn/en/subproduct/hippo

Technical documentation

www.h2gis.org/docs/home

rdf4j.org/documentation

Developer

Atos Convergence Creators

CNRS

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

Initial release

2016

2013

2004

2023

Current release

1703

1.0, May 2023

License

Commercial or Open Source

commercial

Open Source

LGPL 3.0

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.

Implementation language

Java

C++

Server operating systems

Linux

Linux
OS X
Unix
Windows

Linux
macOS

Data scheme

Schema and schema-less with LDAP views

yes

RDF Schemas

Typing

predefined data types such as float or date

optional

yes

Vector, Numeric and String

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

RESTful HTTP API

Supported programming languages

All languages with LDAP bindings

Java

Java
PHP
Python

C++
Java
Python

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

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

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

LDAP bind authentication

yes

based on H2

Role based access control and fine grained access rights

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