DBMS > ClickHouse vs. EJDB vs. Kinetica vs. Kingbase

System Properties Comparison ClickHouse vs. EJDB vs. Kinetica vs. Kingbase

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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.

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Fully vectorized database across both GPUs and CPUs

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

Primary database model

Relational DBMS

Document store

Relational DBMS

Secondary database models

Time Series DBMS

Spatial DBMS
Time Series DBMS

Document store
Spatial DBMS

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

Score	15.88
Rank	#37	Overall
	#22	Relational DBMS

Score	0.13
Rank	#331	Overall
	#46	Document stores

Score	0.42
Rank	#261	Overall
	#120	Relational DBMS

Score	0.44
Rank	#258	Overall
	#117	Relational DBMS

Website

clickhouse.com

github.com/Softmotions/ejdb

www.kinetica.com

www.kingbase.com.cn

Technical documentation

clickhouse.com/docs

github.com/Softmotions/ejdb/blob/master/README.md

docs.kinetica.com

Developer

Clickhouse Inc.

Softmotions

Kinetica

BeiJing KINGBASE Information technologies inc.

Initial release

2016

2012

1999

Current release

v24.6.2.17-stable, July 2024

7.1, August 2021

V8.0, August 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPLv2

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.

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.
DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.

Implementation language

C++

C, C++

C and Java

Server operating systems

FreeBSD
Linux
macOS

server-less

Linux

Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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)

SQL-like DML and DDL statements

Standard with numerous extensions

APIs and other access methods

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

in-process shared library

JDBC
ODBC
RESTful HTTP API

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

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

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

key based and custom

none

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

GPU vRAM or System RAM

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.

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

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