DBMS > ClickHouse vs. Drizzle vs. KairosDB vs. Kdb vs. QuestDB

System Properties Comparison ClickHouse vs. Drizzle vs. KairosDB vs. Kdb vs. QuestDB

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

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.

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Distributed Time Series DBMS based on Cassandra or H2

High performance Time Series DBMS

A high performance open source SQL database for time series data

Primary database model

Relational DBMS

Time Series DBMS

Time Series DBMS
Vector DBMS

Time Series DBMS

Secondary database models

Time Series DBMS

Relational DBMS

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

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	7.55
Rank	#53	Overall
	#3	Time Series DBMS
	#1	Vector DBMS

Score	2.52
Rank	#109	Overall
	#9	Time Series DBMS

Website

clickhouse.com

github.com/kairosdb/kairosdb

kx.com

questdb.io

Technical documentation

Developer

Clickhouse Inc.

Drizzle project, originally started by Brian Aker

Kx Systems, a division of First Derivatives plc

QuestDB Technology Inc

Initial release

2016

2008

2013

2000

kdb was released 2000, kdb+ in 2003

2014

Current release

v24.4.1.2088-stable, May 2024

7.2.4, September 2012

1.2.2, November 2018

3.6, May 2018

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GNU GPL

Open Source

Apache 2.0

commercial

free 32-bit version

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

Implementation language

C++

Java

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

Server operating systems

FreeBSD
Linux
macOS

FreeBSD
Linux
OS X

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free

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.

yes

Secondary indexes

yes

table attribute 'grouped'

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

yes

with proprietary extensions

SQL-like query language (q)

SQL with time-series extensions

APIs and other access methods

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

JDBC

Graphite protocol
HTTP REST
Telnet API

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

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
Rust
Scala

3rd party library

C
C++
Java
PHP

Java
JavaScript

Node.js
PHP
Python

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

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

over HTTP

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

hooks for callbacks inside the server can be used.

yes

with views

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

based on Cassandra

horizontal partitioning

horizontal partitioning (by timestamps)

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication
Source-replica replication

selectable replication factor

based on Cassandra

Source-replica replication

Source-replica replication with eventual consistency

MapReduce

Offers an API for user-defined Map/Reduce methods

similar paradigm used for internal processing

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

Pluggable authentication mechanisms

e.g. LDAP, HTTP

simple password-based access control

rights management via user accounts

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
» more

Relational model with native time series support Column-based storage and time partitioned...
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Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more

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

Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
» more

Financial tick data Industrial IoT Application Metrics Monitoring
» more

Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more

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

Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
» more

Licensing and pricing models

upon request
» more

Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more

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