DBMS > ObjectBox vs. RDF4J vs. Transbase

System Properties Comparison ObjectBox vs. RDF4J vs. Transbase

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Editorial information provided by DB-Engines

Name

Description

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

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

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Object oriented DBMS
Vector DBMS

RDF store

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	1.07
Rank	#174	Overall
	#6	Object oriented DBMS
	#11	Vector DBMS

Score	0.83
Rank	#202	Overall
	#7	RDF stores

Score	0.00
Rank	#379	Overall
	#155	Relational DBMS

Website

github.com/objectbox
objectbox.io

rdf4j.org

www.transaction.de/en/products/transbase.html

Technical documentation

docs.objectbox.io

rdf4j.org/documentation

www.transaction.de/en/products/transbase/features.html

Developer

ObjectBox Limited

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

Transaction Software GmbH

Initial release

2017

2004

1987

Current release

4.0 (May 2024)

Transbase 8.3, 2022

License

Commercial or Open Source

Bindings are released under Apache 2.0

Apache License 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

free development license

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 and C++

Java

C and C++

Server operating systems

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Linux
OS X
Unix
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes, plus "flex" map-like types

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

Proprietary native API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

Java
PHP
Python

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Data sync between devices allowing occasional connected databases to work completely offline

none

Source-replica replication

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

Isolation support depends on the API used

yes

Concurrency

Support for concurrent manipulation of data

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.

User concepts

Access control

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

News

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30 November 2024

IoT, Edge Computing, and Digitalization in Healthcare
22 November 2024

The Embedded Database for C++ and C
11 November 2024

The Critical Role of Databases for Edge AI
11 November 2024

Bi-directional Offline-First Data Sync with MongoDB and ObjectBox
21 October 2024

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