DBMS > Amazon Redshift vs. Trino

System Properties Comparison Amazon Redshift vs. Trino

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

Primary database model

Relational DBMS

Secondary database models

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	14.70
Rank	#36	Overall
	#22	Relational DBMS

Score	5.34
Rank	#60	Overall
	#34	Relational DBMS

Website

aws.amazon.com/redshift

trino.io

Technical documentation

docs.aws.amazon.com/redshift

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

Developer

Amazon (based on PostgreSQL)

Trino Software Foundation

Initial release

2012

2020 rebranded from PrestoSQL

License

Commercial or Open Source

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

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Implementation language

Java

Server operating systems

hosted

Linux
macOS

for devlopment

Data scheme

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.

Secondary indexes

restricted

depending on connected data-source

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

All languages supporting JDBC/ODBC

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

yes, depending on connected data-source

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on connected data-source

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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

SQL standard access control

More information provided by the system vendor

News

73: Wrapping Trino packages with a bow
9 April 2025

Core Principles and Design Practices of OLAP Engines
27 March 2025

72: Keeping the lake clean
17 March 2025

Twenty four
3 March 2025

71: Fake it real good
27 February 2025

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

Increased popularity for consuming DBMS services out of the cloud
2 October 2015, Paul Andlinger

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Recent citations in the news

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30 January 2025, Amazon Web Services

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provided by Google News

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