DBMS > ClickHouse vs. RDF4J vs. Warp 10

System Properties Comparison ClickHouse vs. RDF4J vs. Warp 10

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Editorial information provided by DB-Engines

Name

Description

Column-oriented Relational DBMS powering Yandex

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

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Relational DBMS

RDF store

Time Series DBMS

Secondary database models

Time Series DBMS

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

Score	15.13
Rank	#39	Overall
	#24	Relational DBMS

Score	1.06
Rank	#214	Overall
	#9	RDF stores

Score	0.05
Rank	#385	Overall
	#41	Time Series DBMS

Website

clickhouse.com

rdf4j.org

www.warp10.io

Technical documentation

clickhouse.com/docs

rdf4j.org/documentation

www.warp10.io/content/02_Getting_started

Developer

Clickhouse Inc.

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

SenX

Initial release

2016

2004

2015

Current release

v23.7.4.5-stable, August 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache License 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.

Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.

Implementation language

C++

Java

Server operating systems

FreeBSD
Linux
macOS

Linux
OS X
Unix
Windows

Linux
OS X
Windows

Data scheme

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.

Secondary indexes

yes, when using the MergeTree engine

yes

SQL

Support of SQL

Close to ANSI SQL

APIs and other access methods

HTTP REST
JDBC
ODBC
Proprietary protocol

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP API
Jupyter
WebSocket

Supported programming languages

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Scala

3rd party library

Java
PHP
Python

Server-side scripts

Stored procedures

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

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

Access rights for users and roles

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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