DBMS > ClickHouse vs. DuckDB vs. Elasticsearch

System Properties Comparison ClickHouse vs. DuckDB vs. Elasticsearch

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Editorial information provided by DB-Engines

Name

Description

Column-oriented Relational DBMS powering Yandex

An embeddable, in-process, column-oriented SQL OLAP RDBMS

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Primary database model

Relational DBMS

Search engine

Secondary database models

Time Series DBMS

Document store
Spatial DBMS
Vector DBMS

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

Score	14.97
Rank	#44	Overall
	#28	Relational DBMS

Score	3.06
Rank	#116	Overall
	#60	Relational DBMS

Score	143.75
Rank	#8	Overall
	#1	Search engines

Website

clickhouse.tech

duckdb.org

www.elastic.co/elasticsearch

Technical documentation

clickhouse.tech/docs

duckdb.org/docs

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

Developer

Clickhouse Inc.

Elastic

Initial release

2016

2018

2010

Current release

v23.4.1.1943-stable, April 2023

0.2, August 2020

8.6, January 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

MIT License

Open Source

Elastic License

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++

Java

Server operating systems

FreeBSD
Linux
macOS

server-less

All OS with a Java VM

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

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, when using the MergeTree engine

yes

All search fields are automatically indexed

SQL

Support of SQL

Close to ANSI SQL

yes

SQL-like query language

APIs and other access methods

HTTP REST
JDBC
ODBC
Proprietary protocol

CLI Client
JDBC

Java API
RESTful HTTP/JSON API

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
C++
Go

3rd party driver
Java
Python
R
Ruby

3rd party driver

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Memcached and Redis integration

User concepts

Access control

Access rights for users and roles

More information provided by the system vendor

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2017
2 January 2018, Paul Andlinger, Matthias Gelbmann

Elasticsearch moved into the top 10 most popular database management systems
3 July 2017, Matthias Gelbmann

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

show all

Recent citations in the news

ClickHouse launches ClickHouse Cloud, extends its Series B
6 December 2022, TechCrunch

Aiven launches managed ClickHouse database as a service
13 December 2022, TechTarget

When you try to hire a freelancer to write SQL and all you get is incorrect AI garbage
9 May 2023, The Register

Why Clickhouse is so fast? The Secret to Its Blazing Fast Performance
14 April 2023, Startup.info

How to Install ClickHouse on Ubuntu 22.04 LTS Linux
16 November 2022, linux.how2shout.com

provided by Google News

5 newer data science tools you should be using with Python
17 May 2023, InfoWorld

MotherDuck, DuckDB Labs Founders on Commercializing Open ...
20 April 2023, Madrona Venture Group

MotherDuck secures investment from Andreessen Horowitz to commercialize DuckDB
15 November 2022, TechCrunch

DuckDB, database wrangler used by Google, Facebook, and Airbnb, hits 0.5.0
9 September 2022, The Register

What The Heck Is DuckDB?
26 July 2022, hackernoon.com

provided by Google News

Total Economic Impact™ Study Reveals 293% Three-Year ROI for ...
6 June 2023, Business Wire

Elastic Unveils the Elasticsearch Relevance Engine for Artificial ...
23 May 2023, Business Wire

Somehow Amazon's Open Source Fork of ElasticSearch Has ...
14 May 2023, Slashdot

Building A Log Analytics Solution 10 Times More Cost-Effective ...
15 May 2023, hackernoon.com

Replacing Apache Hive, Elasticsearch and PostgreSQL with Apache ...
19 May 2023, hackernoon.com

provided by Google News

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