DBMS > Trino vs. Vertica

System Properties Comparison Trino vs. Vertica

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Editorial information provided by DB-Engines

Name

Description

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

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Relational DBMS

Column oriented

Secondary database models

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

Spatial DBMS
Time Series DBMS

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

Score	5.18
Rank	#60	Overall
	#34	Relational DBMS

Score	9.85
Rank	#42	Overall
	#26	Relational DBMS

Website

trino.io

www.vertica.com

Technical documentation

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

vertica.com/documentation

Developer

Trino Software Foundation

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2012

2020 rebranded from PrestoSQL

2005

Current release

12.0.3, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Server operating systems

Linux
macOS

for devlopment

Linux

Data scheme

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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

depending on connected data-source

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

yes

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

JDBC
RESTful HTTP API
Trino CLI

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
R
Ruby

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

yes, depending on connected data-source

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

depending on connected data-source

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

depending on connected data-source

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

depending on connected data-source

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

depending on connected data-source

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

depending on connected data-source

yes

In-memory capabilities

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

User concepts

Access control

SQL standard access control

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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

Recent citations in the news

The Perfect AI Storage: Trino From Facebook And Iceberg From Netflix?
30 April 2024, The Next Platform

A look at Presto, Trino SQL query engines
9 August 2022, TechTarget

Trino: The Open-source Data Query Engine That Split from Facebook
30 March 2022, HackerNoon

Query big data with resilience using Trino in Amazon EMR with Amazon EC2 Spot Instances for less cost
4 October 2023, Amazon Web Services

Trino and dbt open source data tools snuggle closer with integrated SaaS
28 April 2023, theregister.com

provided by Google News

Introducing the Future of Data Analysis: A Revolutionary Tool for Vertica Users
25 October 2024, OpenText Blogs

Leveraging Vertica Performance by Reducing CPU System Calls
23 January 2025, Taboola.com

New browser-based query editor for OpenText Core Analytics Database accelerates and simplifies querying your data
25 November 2024, OpenText Blogs

Querying a Vertica data source in Amazon Athena using the Athena Federated Query SDK
11 February 2021, Amazon Web Services

Vertica on Kubernetes
20 June 2024, OpenText Blogs

provided by Google News

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