DBMS > H2 vs. HyperSQL vs. Pinecone vs. Snowflake vs. Trino

System Properties Comparison H2 vs. HyperSQL vs. Pinecone vs. Snowflake vs. Trino

Editorial information provided by DB-Engines

Name

Description

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

A managed, cloud-native vector database

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

Vector 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	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	3.23
Rank	#92	Overall
	#2	Vector DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	4.99
Rank	#65	Overall
	#36	Relational DBMS

Website

Technical documentation

www.h2database.com/html/main.html

hsqldb.org/web/hsqlDocsFrame.html

docs.pinecone.io/docs/overview

docs.snowflake.net/manuals/index.html

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

Social network pages

Developer

Thomas Mueller

Pinecone Systems, Inc

Snowflake Computing Inc.

Trino Software Foundation

Initial release

2005

2001

2019

2014

2012

2020 rebranded from PrestoSQL

Current release

2.2.220, July 2023

2.7.2, June 2023

License

Commercial or Open Source

Open Source

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

Open Source

based on BSD license

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

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

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

String, Number, Boolean

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

Secondary indexes

yes

depending on connected data-source

SQL

Support of SQL

yes

APIs and other access methods

JDBC
ODBC

HTTP API

JDBC via HTTP
JDBC
ODBC

RESTful HTTP API

CLI Client
JDBC
ODBC

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

Java

All languages supporting JDBC/ODBC
Java

Python

JavaScript (Node.js)
Python

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

Java, SQL

user defined functions

yes, depending on connected data-source

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

yes

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

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

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, 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

fine grained access rights according to SQL-standard

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

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...
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News

One busy week to go before Trino Fest 2024
6 June 2024

60: Trino calling AI
22 May 2024

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

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