DBMS > HBase vs. RDF4J

System Properties Comparison HBase vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

Wide-column store based on Apache Hadoop and on concepts of BigTable

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

Primary database model

Wide column store

RDF store

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

Score	43.24
Rank	#23	Overall
	#2	Wide column stores

Score	0.57
Rank	#220	Overall
	#9	RDF stores

Website

hbase.apache.org

rdf4j.org

Technical documentation

hbase.apache.org

rdf4j.org/documentation

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

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

Initial release

2008

2004

Current release

2.3.4, January 2021

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

Java

Server operating systems

Linux
Unix
Windows

using Cygwin

Linux
OS X
Unix
Windows

Data scheme

schema-free, schema definition possible

yes

RDF Schemas

Typing

predefined data types such as float or date

options to bring your own types, AVRO

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

APIs and other access methods

Java API
RESTful HTTP API
Thrift

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Coprocessors in Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Single row ACID (across millions of columns)

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

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

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

More information provided by the system vendor

Specific characteristics

Apache HBase is the leading NoSQL, distributed database management system, well suited...
» more

Competitive advantages

No single point of failure ensures very high availability with multiple customers...
» more

Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
» more

Key customers

Apple, Salesforce, Cerner, Allegis Group, Bloomberg, Airtel, Thomson Reuters, Dish,...
» more

Market metrics

#1 largest NoSQL database by revenue
» more

Licensing and pricing models

Apache license P ricing for commercial distribution provided by Cloudera and available...
» more

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More resources

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