DBMS > Apache Druid vs. ClickHouse vs. InfluxDB

System Properties Comparison Apache Druid vs. ClickHouse vs. InfluxDB

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Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Column-oriented Relational DBMS powering Yandex

DBMS for storing time series, events and metrics

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Time Series DBMS

Spatial DBMS

with GEO package

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

Score	3.33
Rank	#104	Overall
	#53	Relational DBMS
	#7	Time Series DBMS

Score	16.96
Rank	#39	Overall
	#24	Relational DBMS

Score	28.12
Rank	#28	Overall
	#1	Time Series DBMS

Website

druid.apache.org

clickhouse.com

www.influxdata.com/products/influxdb-overview

Technical documentation

druid.apache.org/docs/latest/design

clickhouse.com/docs

docs.influxdata.com/influxdb

Developer

Apache Software Foundation and contributors

Clickhouse Inc.

Initial release

2012

2016

2013

Current release

28.0.0, November 2023

v23.7.4.5-stable, August 2023

2.7.1, April 2023

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache 2.0

Open Source

MIT-License; commercial enterprise version 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.

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

Implementation language

Java

C++

Server operating systems

Linux
OS X
Unix

FreeBSD
Linux
macOS

Linux
OS X

through Homebrew

Data scheme

yes

schema-less columns are supported

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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

SQL

Support of SQL

SQL for querying

Close to ANSI SQL

SQL-like query language

APIs and other access methods

JDBC
RESTful HTTP/JSON API

HTTP REST
JDBC
ODBC
Proprietary protocol

HTTP API
JSON over UDP

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

in enterprise version only

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

selectable replication factor

in enterprise version only

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate 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

Depending on used storage engine

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Access rights for users and roles

simple rights management via user accounts

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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