DBMS > Infobright vs. Postgres-XL vs. ToroDB vs. Trino

System Properties Comparison Infobright vs. Postgres-XL vs. ToroDB vs. Trino

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Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

A MongoDB-compatible JSON document store, built on top of PostgreSQL

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

Primary database model

Relational DBMS

Document store

Relational DBMS

Secondary database models

Document store
Spatial 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	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	5.00
Rank	#66	Overall
	#36	Relational DBMS

Website

ignitetech.com/softwarelibrary/infobrightdb

www.postgres-xl.org

github.com/torodb/server

trino.io

Technical documentation

www.postgres-xl.org/documentation

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

Social network pages

Developer

Ignite Technologies Inc.; formerly InfoBright Inc.

8Kdata

Trino Software Foundation

Initial release

2005

2014

since 2012, originally named StormDB

2016

2012

2020 rebranded from PrestoSQL

Current release

10 R1, October 2018

License

Commercial or Open Source

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

Mozilla public license

Open Source

AGPL-V3

Open Source

Apache Version 2.0

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.

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
Windows

Linux
macOS

All OS with a Java 7 VM

Linux
macOS

for devlopment

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

XML type, but no XML query functionality

Secondary indexes

Knowledge Grid Technology used instead

yes

depending on connected data-source

SQL

Support of SQL

yes

distributed, parallel query execution

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

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

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

yes, depending on connected data-source

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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

Eventual Consistency
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

MVCC

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

exploiting MySQL or PostgreSQL frontend capabilities

fine grained access rights according to SQL-standard

Access rights for users and roles

SQL standard access control

More information provided by the system vendor

Specific characteristics

Trino is the fastest open source, massively parallel processing SQL query engine...
» more

Competitive advantages

High performance analtyics and data processing of very large data sets Powerful ANSI...
» more

Typical application scenarios

Performant analytics query engine for data warehouses, data lakes, and data lakehouses...
» more

Key customers

Trino is widely adopted across the globe as freely-available open source software....
» more

Market metrics

33000+ commits in GitHub 8200+ stargazers in GitHub 1200+ pull requests merged in...
» more

Licensing and pricing models

Trino is an open source project and usage is therefore free. Commercial offerings...
» more

News

Big names round out the Trino Fest 2024 lineup
8 May 2024

59: Querying Trino with Java and jOOQ
24 April 2024

A sneak peek of Trino Fest 2024
15 April 2024

Time travel in Delta Lake connector
11 April 2024

58: Understanding your users with Trino and Mitzu
4 April 2024

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

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More resources

Recent citations in the news

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7 September 2023, Datanami

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A look at Presto, Trino SQL query engines
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30 March 2022, hackernoon.com

provided by Google News

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