DBMS > RDF4J vs. Realm vs. Teradata Aster

System Properties Comparison RDF4J vs. Realm vs. Teradata Aster

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Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

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

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Platform for big data analytics on multistructured data sources and types

Primary database model

RDF store

Document store

Relational DBMS

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

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Score	7.71
Rank	#52	Overall
	#9	Document stores

Website

rdf4j.org

realm.io

Technical documentation

rdf4j.org/documentation

realm.io/docs

Developer

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

Realm, acquired by MongoDB in May 2019

Teradata

Initial release

2004

2014

2005

License

Commercial or Open Source

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

Linux
OS X
Unix
Windows

Android
Backend: server-less
iOS
Windows

Linux

Data scheme

yes

RDF Schemas

yes

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

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.

yes

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

Java
PHP
Python

.Net
Java

with Android only
Objective-C
React Native
Swift

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

runs within the applications so server-side scripts are unnecessary

R packages

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

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

In-Memory realm

User concepts

Access control

yes

fine grained access rights according to SQL-standard

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