DBMS > Hypertable vs. InterSystems Caché vs. RDF4J vs. RocksDB

System Properties Comparison Hypertable vs. InterSystems Caché vs. RDF4J vs. RocksDB

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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.

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

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

A multi-model DBMS and application server

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Wide column store

Key-value store
Object oriented DBMS
Relational DBMS

RDF store

Key-value store

Secondary database models

Document store

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

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Website

www.intersystems.com/products/cache

rdf4j.org

rocksdb.org

Technical documentation

docs.intersystems.com

rdf4j.org/documentation

github.com/facebook/rocksdb/wiki

Developer

Hypertable Inc.

InterSystems

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

Facebook, Inc.

Initial release

2009

1997

2004

2013

Current release

0.9.8.11, March 2016

2018.1.4, May 2020

8.11.4, April 2024

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license available

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

C++

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

Linux

Data scheme

schema-free

depending on used data model

yes

RDF Schemas

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.

yes

Secondary indexes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

APIs and other access methods

C++ API
Thrift

.NET Client API
JDBC
ODBC
RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

C++ API
Java API

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

C#
C++
Java

Java
PHP
Python

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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.

yes

User concepts

Access control

Access rights for users, groups and roles

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