DBMS > Apache Kylin vs. ClickHouse vs. Hive

System Properties Comparison Apache Kylin vs. ClickHouse vs. Hive

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Editorial information provided by DB-Engines

Name

Description

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

Column-oriented Relational DBMS powering Yandex

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Primary database model

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	1.39
Rank	#183	Overall
	#88	Relational DBMS

Score	16.96
Rank	#39	Overall
	#24	Relational DBMS

Score	69.41
Rank	#18	Overall
	#12	Relational DBMS

Website

kylin.apache.org

clickhouse.com

hive.apache.org

Technical documentation

kylin.apache.org/docs

clickhouse.com/docs

cwiki.apache.org/confluence/display/Hive/Home

Developer

Apache Software Foundation, originally contributed from eBay Inc

Clickhouse Inc.

Apache Software Foundation

initially developed by Facebook

Initial release

2015

2016

2012

Current release

3.1.0, July 2020

v23.7.4.5-stable, August 2023

3.1.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Apache Version 2

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

Java

C++

Java

Server operating systems

Linux

FreeBSD
Linux
macOS

All OS with a Java VM

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.

Secondary indexes

yes

yes, when using the MergeTree engine

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

Close to ANSI SQL

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

HTTP REST
JDBC
ODBC
Proprietary protocol

JDBC
ODBC
Thrift

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

C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

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

Access rights for users, groups and roles

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