DBMS > ClickHouse vs. MonetDB vs. QuestDB

System Properties Comparison ClickHouse vs. MonetDB vs. QuestDB

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Editorial information provided by DB-Engines

Name

Description

Column-oriented Relational DBMS powering Yandex

A relational database management system that stores data in columns

A high performance open source SQL database for time series data

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Time Series DBMS

Document store
Spatial DBMS

Relational DBMS

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

Score	16.96
Rank	#39	Overall
	#24	Relational DBMS

Score	2.20
Rank	#143	Overall
	#67	Relational DBMS

Score	2.31
Rank	#137	Overall
	#10	Time Series DBMS

Website

clickhouse.com

www.monetdb.org

questdb.io

Technical documentation

clickhouse.com/docs

www.monetdb.org/Documentation

questdb.io/docs

Developer

Clickhouse Inc.

MonetDB BV

QuestDB Technology Inc

Initial release

2016

2004

2014

Current release

v23.7.4.5-stable, August 2023

Jul2021-SP2, July 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Mozilla Public License 2.0

Open Source

Apache 2.0

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

C++

Java (Zero-GC), C++, Rust

Server operating systems

FreeBSD
Linux
macOS

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free via InfluxDB Line Protocol

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

SQL

Support of SQL

Close to ANSI SQL

yes

SQL 2003 with some extensions

SQL with time-series extensions

APIs and other access methods

HTTP REST
JDBC
ODBC
Proprietary protocol

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

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++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

Server-side scripts

Stored procedures

yes, in SQL, C, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding via remote tables

horizontal partitioning (by timestamps)

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication available in experimental status

Source-replica replication with eventual consistency

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

yes

Transaction concepts

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

ACID

ACID for single-table writes

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

through memory mapped files

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Relational model with native time series support Column-based storage and time partitioned...
» more

Competitive advantages

High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more

Typical application scenarios

Financial tick data Industrial IoT Application Metrics Monitoring
» more

Key customers

Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more

Licensing and pricing models

Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more

News

Moving average signals with QuestDB, Grafana and Coinbase
8 December 2023

QuestDB Release Week #4
24 November 2023

Building a faster hash table for high performance SQL joins
23 November 2023

Is all data time series data?
21 November 2023

Solving duplicate data with performant deduplication
16 November 2023

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