DBMS > ObjectBox vs. RDF4J vs. Yaacomo vs. Yanza

System Properties Comparison ObjectBox vs. RDF4J vs. Yaacomo vs. Yanza

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Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

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

Description

Extremely fast embedded database for small devices, IoT and Mobile

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

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Time Series DBMS for IoT Applications

Primary database model

Secondary database models

Time Series DBMS

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

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

objectbox.io

rdf4j.org

yaacomo.com

yanza.com

Technical documentation

docs.objectbox.io

rdf4j.org/documentation

Developer

ObjectBox Limited

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

Q2WEB GmbH

Yanza

Initial release

2017

2004

2009

2015

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C and C++

Java

Server operating systems

Android
iOS
Linux
macOS
Windows

Linux
OS X
Unix
Windows

Android
Linux
Windows

Windows

Data scheme

yes

RDF Schemas

yes

schema-free

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.

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

JDBC
ODBC

HTTP API

Supported programming languages

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

Java
PHP
Python

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

online/offline synchronization between client and server

none

Source-replica replication

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

Isolation support depends on the API used

ACID

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.

yes

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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More resources

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21 June 2019, 1E9

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