DBMS > ClickHouse vs. GBase vs. Vitess

System Properties Comparison ClickHouse vs. GBase vs. Vitess

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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.

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Relational DBMS

Secondary database models

Time Series DBMS

Document store
Spatial DBMS

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

Score	18.56
Rank	#30	Overall
	#18	Relational DBMS

Score	1.24
Rank	#164	Overall
	#74	Relational DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Website

clickhouse.com

www.gbase.cn

vitess.io

Technical documentation

clickhouse.com/docs

vitess.io/docs

Developer

Clickhouse Inc.

General Data Technology Co., Ltd.

The Linux Foundation, PlanetScale

Initial release

2016

2004

2013

Current release

v24.6.2.17-stable, July 2024

GBase 8a, GBase 8s, GBase 8c

15.0.2, December 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2.0, commercial licenses available

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++

C, Java, Python

Server operating systems

FreeBSD
Linux
macOS

Linux

Docker
Linux
macOS

Data scheme

yes

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

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

Standard with numerous extensions

yes

with proprietary extensions

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
MySQL protocol
ODBC

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

user defined functions

yes

proprietary syntax

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Users with fine-grained authorization concept

no user groups or roles

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More resources

Recent citations in the news

ClickHouse Announces Strategic Collaboration Agreement with AWS to Advance Real-Time Data Analytics and Generative AI Innovation
10 December 2024, Business Wire

A Beginner’s Guide to ClickHouse Database
13 September 2024, KDnuggets

Real-time database startup ClickHouse acquires PeerDB to expand its Postgres support
30 July 2024, TechCrunch

Azur Games migrates all game analytics data to ClickHouse Cloud on AWS
16 July 2024, AWS Blog

Database startup ClickHouse Announces PeerDB Acquistion
31 July 2024, Tech Times

provided by Google News

Massively Scaling MySQL Using Vitess
19 February 2019, InfoQ.com

Update CNCF’s Vitess Scales MySQL with the Help of Kubernetes
29 March 2022, InApps Technology

PlanetScale Announces Developer-First, Instantly-Provisioned and Infinitely-Scalable Database for Companies of All Sizes
18 May 2021, Business Wire

How PlanetScaleDB Deploys Vitess to Run Production Databases on Kubernetes
14 August 2020, The New Stack

PlanetScale review: Horizontally scalable MySQL in the cloud
1 September 2021, InfoWorld

provided by Google News

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