DBMS > Blueflood vs. H2 vs. Hypertable vs. RDF4J

System Properties Comparison Blueflood vs. H2 vs. Hypertable vs. RDF4J

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Scalable TimeSeries DBMS based on Cassandra

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

An open source BigTable implementation based on distributed file systems such as Hadoop

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

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

blueflood.io

www.h2database.com

rdf4j.org

Technical documentation

github.com/rax-maas/blueflood/wiki

www.h2database.com/html/main.html

rdf4j.org/documentation

Developer

Rackspace

Thomas Mueller

Hypertable Inc.

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

Initial release

2013

2005

2009

2004

Current release

2.2.220, July 2023

0.9.8.11, March 2016

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

GNU version 3. Commercial license available

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

Java

C++

Java

Server operating systems

Linux
OS X

All OS with a Java VM

Linux
OS X
Windows

an inofficial Windows port is available

Linux
OS X
Unix
Windows

Data scheme

predefined scheme

yes

schema-free

yes

RDF Schemas

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

APIs and other access methods

HTTP REST

JDBC
ODBC

C++ API
Thrift

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Java

C++
Java
Perl
PHP
Python
Ruby

Java
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

With clustering: 2 database servers on different computers operate on identical copies of a database

selectable replication factor on file system level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

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