DBMS > Citus vs. Kdb vs. MySQL vs. Tarantool

System Properties Comparison Citus vs. Kdb vs. MySQL vs. Tarantool

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

High performance Time Series DBMS

Widely used open source RDBMS

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

Primary database model

Relational DBMS

Time Series DBMS
Vector DBMS

Relational DBMS

Key/Value like access via memcached API

Document store
Key-value store
Relational DBMS

Secondary database models

Document store

Relational DBMS

Document store
Spatial DBMS

Spatial DBMS

with Tarantool/GIS extension

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

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

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

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	1.72
Rank	#144	Overall
	#25	Document stores
	#25	Key-value stores
	#66	Relational DBMS

Website

Technical documentation

docs.citusdata.com

code.kx.com

dev.mysql.com/doc

www.tarantool.io/en/doc

Developer

Kx Systems, a division of First Derivatives plc

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2010

2000

kdb was released 2000, kdb+ in 2003

1995

2008

Current release

8.1, December 2018

3.6, May 2018

8.4.0, April 2024

2.10.0, May 2022

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

commercial

free 32-bit version

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

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 MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

C and C++

Server operating systems

Linux

Linux
OS X
Solaris
Windows

FreeBSD
Linux
OS X
Solaris
Windows

BSD
Linux
macOS

Data scheme

yes

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

Typing

predefined data types such as float or date

yes

string, double, decimal, uuid, integer, blob, boolean, datetime

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

specific XML type available, but no XML query functionality

yes

Secondary indexes

yes

table attribute 'grouped'

yes

SQL

Support of SQL

yes

standard, with numerous extensions

SQL-like query language (q)

yes

with proprietary extensions

Full-featured ANSI SQL support

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

ADO.NET
JDBC
ODBC
Proprietary native API

Open binary protocol

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

user defined functions

yes

proprietary syntax

Lua, C and SQL stored procedures

Triggers

yes

with views

yes

yes, before/after data modification events, on replication events, client session events

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

Source-replica replication

Multi-source replication
Source-replica replication

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

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

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes, cooperative multitasking

Durability

Support for making data persistent

yes

yes, write ahead logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

yes, full featured in-memory storage engine with persistence

User concepts

Access control

fine grained access rights according to SQL-standard

rights management via user accounts

Users with fine-grained authorization concept

no user groups or roles

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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...
» more

Typical application scenarios

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

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...
» more

Licensing and pricing models

upon request
» more

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.