DBMS > Altibase vs. LeanXcale vs. RDF4J vs. RisingWave

System Properties Comparison Altibase vs. LeanXcale vs. RDF4J vs. RisingWave

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Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

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

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

Primary database model

Relational DBMS

Key-value store
Relational DBMS

RDF store

Relational DBMS

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

Score	1.02
Rank	#189	Overall
	#88	Relational DBMS

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	0.64
Rank	#238	Overall
	#110	Relational DBMS

Website

altibase.com

www.leanxcale.com

rdf4j.org

www.risingwave.com/database

Technical documentation

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

rdf4j.org/documentation

docs.risingwave.com/docs/current/intro

Developer

Altibase

LeanXcale

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

RisingWave Labs

Initial release

1999

2015

2004

2022

Current release

v7.3, 2023, August 2023

1.2, September 2023

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache Version 2.0

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++

Java

Rust

Server operating systems

AIX
HP-UX
Linux

Linux
OS X
Unix
Windows

Docker
Linux
macOS

Data scheme

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

Standard SQL-types and JSON

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

through Apache Derby

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

JDBC
PostgreSQL wire protocol

Supported programming languages

C
C++
Java

C
Java
Scala

Java
PHP
Python

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

stored procedures and stored functions

yes

UDFs in Python or Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

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

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

Users and Roles

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