DBMS > Altibase vs. RDF4J vs. RocksDB vs. Transwarp Hippo

System Properties Comparison Altibase vs. RDF4J vs. RocksDB vs. Transwarp Hippo

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Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

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)

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

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

Score	0.87
Rank	#200	Overall
	#93	Relational DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	2.84
Rank	#97	Overall
	#16	Key-value stores

Score	0.00
Rank	#385	Overall
	#16	Vector DBMS

Website

altibase.com

rdf4j.org

rocksdb.org

www.transwarp.cn/en/subproduct/hippo

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

rdf4j.org/documentation

github.com/facebook/rocksdb/wiki

Developer

Altibase

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

Facebook, Inc.

Initial release

1999

2004

2013

2023

Current release

v7.3, 2023, August 2023

9.4.0, June 2024

1.0, May 2023

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

BSD

commercial

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

C++

Java

C++

Server operating systems

AIX
HP-UX
Linux

Linux
OS X
Unix
Windows

Linux

Linux
macOS

Data scheme

yes

RDF Schemas

schema-free

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

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

ANSI SQL-92

APIs and other access methods

JDBC
ODBC
Proprietary protocol

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

C++ API
Java API

RESTful HTTP API

Supported programming languages

C
C++
Java

Java
PHP
Python

C
C++
Go
Java
Perl
Python
Ruby

C++
Java
Python

Server-side scripts

Stored procedures

stored procedures and stored functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

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

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

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

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