DBMS > Fauna vs. H2 vs. Trino

System Properties Comparison Fauna vs. H2 vs. Trino

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Editorial information provided by DB-Engines

Name

Description

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

Primary database model

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Relational DBMS

Secondary database models

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	1.45
Rank	#144	Overall
	#25	Document stores
	#13	Graph DBMS
	#65	Relational DBMS
	#14	Time Series DBMS

Score	7.26
Rank	#45	Overall
	#28	Relational DBMS

Score	5.34
Rank	#60	Overall
	#34	Relational DBMS

Website

fauna.com

www.h2database.com

trino.io

Technical documentation

docs.fauna.com

www.h2database.com/html/main.html

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

Developer

Fauna, Inc.

Thomas Mueller

Trino Software Foundation

Initial release

2014

2005

2012

2020 rebranded from PrestoSQL

Current release

2.2.220, July 2023

License

Commercial or Open Source

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

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.

Implementation language

Scala

Java

Server operating systems

hosted

All OS with a Java VM

Linux
macOS

for devlopment

Data scheme

schema-free

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

yes

depending on connected data-source

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

Java

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures and User-Defined Functions

yes, depending on connected data-source

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

consistent hashing

none

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

With clustering: 2 database servers on different computers operate on identical copies of a database

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

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

yes, multi-version concurrency control (MVCC)

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

Identity management, authentication, and 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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