DBMS > gStore vs. Interbase vs. IRONdb vs. RDF4J

System Properties Comparison gStore vs. Interbase vs. IRONdb vs. RDF4J

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Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

A native Graph DBMS to store and maintain very large RDF datasets.

Light-weight proven RDBMS

originally from Borland

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

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

Primary database model

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

Score	0.04
Rank	#359	Overall
	#37	Graph DBMS
	#18	RDF stores

Score	4.61
Rank	#72	Overall
	#39	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

en.gstore.cn

www.embarcadero.com/products/interbase

www.circonus.com/solutions/time-series-database/

rdf4j.org

Technical documentation

en.gstore.cn/#/enDocs

docs.embarcadero.com/products/interbase

docs.circonus.com/irondb/category/getting-started

rdf4j.org/documentation

Developer

Embarcadero

Circonus LLC.

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

Initial release

2016

1984

2017

2004

Current release

1.2, November 2023

InterBase 2020, December 2019

V0.10.20, January 2018

License

Commercial or Open Source

Open Source

BSD

commercial

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++

C and C++

Java

Server operating systems

Linux

Android
iOS
Linux
OS X
Windows

Linux

Linux
OS X
Unix
Windows

Data scheme

schema-free and OWL/RDFS-schema support

yes

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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.

export as XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (Circonus Analytics Query Language: CAQL)

APIs and other access methods

HTTP API
SPARQL 1.1

ADO.NET
JDBC
ODBC

HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C++
Java
JavaScript (Node.js)
PHP
Python

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Interbase procedure and trigger language

yes, in Lua

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Automatic, metric affinity per node

none

Replication methods

Methods for redundantly storing data on multiple nodes

Interbase Change Views

configurable replication factor, datacenter aware

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

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

Users, roles and permissions, Role-Based Access Control (RBAC) supported

fine grained access rights according to SQL-standard

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