DBMS > H2GIS vs. Ingres vs. Microsoft Azure Table Storage vs. RDF4J

System Properties Comparison H2GIS vs. Ingres vs. Microsoft Azure Table Storage vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

Spatial extension of H2

Well established RDBMS

A Wide Column Store for rapid development using massive semi-structured datasets

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

Primary database model

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	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

www.h2gis.org

www.actian.com/databases/ingres

azure.microsoft.com/en-us/services/storage/tables

rdf4j.org

Technical documentation

www.h2gis.org/docs/home

docs.actian.com/ingres

rdf4j.org/documentation

Developer

CNRS

Actian Corporation

Microsoft

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

Initial release

2013

1974

originally developed at University Berkely in early 1970s

2012

2004

Current release

11.2, May 2022

License

Commercial or Open Source

Open Source

LGPL 3.0

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

hosted

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

RDF Schemas

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Java

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Java
PHP
Python

Server-side scripts

Stored procedures

yes

based on H2

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

Ingres Replicator

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

optimistic locking

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

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

fine grained access rights according to SQL-standard

Access rights based on private key authentication or shared access signatures

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