DBMS > Citus vs. Kdb vs. Snowflake vs. Trino

System Properties Comparison Citus vs. Kdb vs. Snowflake vs. Trino

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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

Cloud-based data warehousing service for structured and semi-structured data

Fast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL

Primary database model

Relational DBMS

Time Series DBMS
Vector DBMS

Relational DBMS

Secondary database models

Document store

Relational DBMS

Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store

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	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	5.00
Rank	#66	Overall
	#36	Relational DBMS

Website

Technical documentation

docs.citusdata.com

code.kx.com

docs.snowflake.net/manuals/index.html

trino.io/broadcast
trino.io/docs/current

Social network pages

Developer

Kx Systems, a division of First Derivatives plc

Snowflake Computing Inc.

Trino Software Foundation

Initial release

2010

2000

kdb was released 2000, kdb+ in 2003

2014

2012

2020 rebranded from PrestoSQL

Current release

8.1, December 2018

3.6, May 2018

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

commercial

free 32-bit version

commercial

Open Source

Apache Version 2.0

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.

Starburst Galaxy offers a feature-rich user interface to connect all your data sources, manage your Trino clusters, and query your data.

Implementation language

Java

Server operating systems

Linux

Linux
OS X
Solaris
Windows

hosted

Linux
macOS

for devlopment

Data scheme

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

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

specific XML type available, but no XML query functionality

yes

Secondary indexes

yes

table attribute 'grouped'

depending on connected data-source

SQL

Support of SQL

yes

standard, with numerous extensions

SQL-like query language (q)

yes

APIs and other access methods

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

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

CLI Client
JDBC
ODBC

JDBC
RESTful HTTP API
Trino CLI

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

JavaScript (Node.js)
Python

Go
Java
JavaScript (Node.js)
Python
R
Ruby

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, depending on connected data-source

Triggers

yes

with views

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

yes

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

Source-replica replication

yes

depending on connected data-source

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

depending on connected data-source

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

depending on connected data-source

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

rights management via user accounts

Users with fine-grained authorization concept, user roles and pluggable authentication

SQL standard access control

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
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Trino is the fastest open source, massively parallel processing SQL query engine...
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Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
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High performance analtyics and data processing of very large data sets Powerful ANSI...
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Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
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Performant analytics query engine for data warehouses, data lakes, and data lakehouses...
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Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
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Trino is widely adopted across the globe as freely-available open source software....
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Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
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33000+ commits in GitHub 8200+ stargazers in GitHub 1200+ pull requests merged in...
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Licensing and pricing models

upon request
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Trino is an open source project and usage is therefore free. Commercial offerings...
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News

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8 May 2024

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15 April 2024

Time travel in Delta Lake connector
11 April 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.