DBMS > ClickHouse vs. Firebird vs. Kdb vs. Rockset

System Properties Comparison ClickHouse vs. Firebird vs. Kdb vs. Rockset

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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

High performance Time Series DBMS

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Relational DBMS

Time Series DBMS
Vector DBMS

Document store

Secondary database models

Time Series DBMS

Relational DBMS

Relational DBMS
Search engine

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

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	20.50
Rank	#30	Overall
	#18	Relational DBMS

Score	7.71
Rank	#49	Overall
	#2	Time Series DBMS
	#1	Vector DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Website

Technical documentation

clickhouse.com/docs

www.firebirdsql.org/en/reference-manuals

code.kx.com

docs.rockset.com

Developer

Clickhouse Inc.

Firebird Foundation

Kx Systems, a division of First Derivatives plc

Rockset

Initial release

2016

2000

As fork of Borland's InterBase

2000

kdb was released 2000, kdb+ in 2003

2019

Current release

v24.4.1.2088-stable, May 2024

5.0.0, January 2024

3.6, May 2018

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Initial Developer's Public License

commercial

free 32-bit version

commercial

Cloud-based only

Only available as a cloud service

yes

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++

C and C++

C++

Server operating systems

FreeBSD
Linux
macOS

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux
OS X
Solaris
Windows

hosted

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

dynamic typing

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

ingestion from XML files supported

Secondary indexes

yes

table attribute 'grouped'

all fields are automatically indexed

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

yes

SQL-like query language (q)

Read-only SQL queries, including JOINs

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

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

HTTP REST

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

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

PSQL

user defined functions

Triggers

yes

with views

Partitioning methods

Methods for storing different data on different nodes

key based and custom

none

horizontal partitioning

Automatic 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

yes

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

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

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

rights management via user accounts

Access rights for users and organizations can be defined via Rockset console

More information provided by the system vendor

Specific characteristics

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

Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
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Key customers

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

Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
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Licensing and pricing models

upon request
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