DBMS > ClickHouse vs. Firebird vs. Kinetica vs. SWC-DB

System Properties Comparison ClickHouse vs. Firebird vs. Kinetica vs. SWC-DB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

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.

Firebird is an open source RDBMS forked from Borland's InterBase

Fully vectorized database across both GPUs and CPUs

A high performance, scalable Wide Column DBMS

Primary database model

Relational DBMS

Wide column store

Secondary database models

Time Series DBMS

Spatial DBMS
Time Series DBMS

Time Series DBMS

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

Score	15.88
Rank	#37	Overall
	#22	Relational DBMS

Score	19.46
Rank	#30	Overall
	#18	Relational DBMS

Score	0.42
Rank	#261	Overall
	#120	Relational DBMS

Score	0.01
Rank	#378	Overall
	#13	Wide column stores

Website

clickhouse.com

www.firebirdsql.org

www.kinetica.com

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

clickhouse.com/docs

www.firebirdsql.org/en/reference-manuals

docs.kinetica.com

Developer

Clickhouse Inc.

Firebird Foundation

Kinetica

Alex Kashirin

Initial release

2016

2000

As fork of Borland's InterBase

2012

2020

Current release

v24.6.2.17-stable, July 2024

5.0.1, August 2024

7.1, August 2021

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Initial Developer's Public License

commercial

Open Source

GPL V3

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.

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

Implementation language

C++

C and C++

C, C++

C++

Server operating systems

FreeBSD
Linux
macOS

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux

Data scheme

yes

schema-free

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

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

yes

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

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

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

JDBC
ODBC
RESTful HTTP API

Proprietary protocol
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
Rust
Scala

3rd party library

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

C++

Server-side scripts

Stored procedures

yes

PSQL

user defined functions

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

Partitioning methods

Methods for storing different data on different nodes

key based and custom

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Features a multi-generational MVCC architecture, readers do not block writers

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

GPU vRAM or System RAM

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.

Users with fine-grained authorization concept

Access rights for users and roles on table level

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.