DBMS > HyperSQL vs. Microsoft SQL Server vs. Sphinx vs. Trino

System Properties Comparison HyperSQL vs. Microsoft SQL Server vs. Sphinx vs. Trino

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Microsofts flagship relational DBMS

Open source search engine for searching in data from different sources, e.g. relational databases

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

Primary database model

Relational DBMS

Search engine

Relational DBMS

Secondary database models

Document store
Graph DBMS
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	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	5.00
Rank	#66	Overall
	#36	Relational DBMS

Website

hsqldb.org

www.microsoft.com/en-us/sql-server

sphinxsearch.com

trino.io

Technical documentation

hsqldb.org/web/hsqlDocsFrame.html

learn.microsoft.com/en-US/sql/sql-server

sphinxsearch.com/docs

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

Social network pages

Developer

Microsoft

Sphinx Technologies Inc.

Trino Software Foundation

Initial release

2001

1989

2001

2012

2020 rebranded from PrestoSQL

Current release

2.7.2, June 2023

SQL Server 2022, November 2022

3.5.1, February 2023

License

Commercial or Open Source

Open Source

based on BSD license

commercial

restricted free version is available

Open Source

GPL version 2, commercial licence available

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

C++

Java

Server operating systems

All OS with a Java VM

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

Linux
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

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.

yes

Secondary indexes

yes

full-text index on all search fields

depending on connected data-source

SQL

Support of SQL

yes

SQL-like query language (SphinxQL)

yes

APIs and other access methods

HTTP API

JDBC via HTTP
JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Proprietary protocol

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

All languages supporting JDBC/ODBC
Java

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

Java, SQL

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes, depending on connected data-source

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

Partitioning is done manually, search queries against distributed index is supported

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, but depending on the SQL-Server Edition

none

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

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

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

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

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

57: Seeing clearly with OpenTelemetry
14 March 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.