DBMS > ClickHouse vs. GBase vs. Infobright vs. RDFox

System Properties Comparison ClickHouse vs. GBase vs. Infobright vs. RDFox

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Editorial information provided by DB-Engines

Name

Description

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

High performance knowledge graph and semantic reasoning engine

Primary database model

Relational DBMS

Graph DBMS
RDF store

Secondary database models

Time Series DBMS

Relational DBMS

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

Score	15.88
Rank	#37	Overall
	#22	Relational DBMS

Score	1.11
Rank	#173	Overall
	#78	Relational DBMS

Score	0.88
Rank	#198	Overall
	#92	Relational DBMS

Score	0.22
Rank	#305	Overall
	#25	Graph DBMS
	#15	RDF stores

Website

clickhouse.com

www.gbase.cn

ignitetech.com/softwarelibrary/infobrightdb

www.oxfordsemantic.tech

Technical documentation

clickhouse.com/docs

docs.oxfordsemantic.tech

Developer

Clickhouse Inc.

General Data Technology Co., Ltd.

Ignite Technologies Inc.; formerly InfoBright Inc.

Oxford Semantic Technologies

Initial release

2016

2004

2005

2017

Current release

v24.6.2.17-stable, July 2024

GBase 8a, GBase 8s, GBase 8c

6.0, Septermber 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

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.

DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.

Implementation language

C++

C, Java, Python

C++

Server operating systems

FreeBSD
Linux
macOS

Linux

Linux
Windows

Linux
macOS
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.

yes

Secondary indexes

yes

Knowledge Grid Technology used instead

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

Standard with numerous extensions

yes

APIs and other access methods

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

ADO.NET
C API
JDBC
ODBC

ADO.NET
JDBC
ODBC

RESTful HTTP API
SPARQL 1.1

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
Rust
Scala

3rd party library

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
Java

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

key based and custom

horizontal partitioning (by range, list and hash) and vertical partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

yes

Source-replica replication

replication via a shared file system

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

yes

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Roles, resources, and access types

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