DBMS > Altibase vs. Databend vs. EXASOL vs. RDF4J

System Properties Comparison Altibase vs. Databend vs. EXASOL vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

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

Primary database model

Relational DBMS

RDF store

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

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	0.30
Rank	#287	Overall
	#130	Relational DBMS

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

altibase.com

github.com/datafuselabs/databend
www.databend.com

www.exasol.com

rdf4j.org

Technical documentation

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

docs.databend.com

www.exasol.com/resources

rdf4j.org/documentation

Developer

Altibase

Databend Labs

Exasol

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

Initial release

1999

2021

2000

2004

Current release

v7.3, 2023, August 2023

1.0.59, April 2023

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Apache Version 2.0

commercial

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

C++

Rust

Java

Server operating systems

AIX
HP-UX
Linux

hosted
Linux
macOS

Linux
OS X
Unix
Windows

Data scheme

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

SQL

Support of SQL

ANSI SQL-92

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol

CLI Client
JDBC
RESTful HTTP API

.Net
JDBC
ODBC
WebSocket

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C
C++
Java

Go
Java
JavaScript (Node.js)
Python
Rust

Java
Lua
Python
R

Java
PHP
Python

Server-side scripts

Stored procedures

stored procedures and stored functions

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

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

yes

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles

Access rights for users, groups and roles according to SQL-standard

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