DBMS > Datomic vs. Microsoft SQL Server vs. RDFox vs. Trino

System Properties Comparison Datomic vs. Microsoft SQL Server vs. RDFox vs. Trino

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Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Microsofts flagship relational DBMS

High performance knowledge graph and semantic reasoning engine

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

Primary database model

Relational DBMS

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational 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	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.23
Rank	#308	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	5.00
Rank	#66	Overall
	#36	Relational DBMS

Website

www.datomic.com

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

www.oxfordsemantic.tech

trino.io

Technical documentation

docs.datomic.com

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

docs.oxfordsemantic.tech

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

Social network pages

Developer

Cognitect

Microsoft

Oxford Semantic Technologies

Trino Software Foundation

Initial release

2012

1989

2017

2012

2020 rebranded from PrestoSQL

Current release

1.0.6735, June 2023

SQL Server 2022, November 2022

6.0, Septermber 2022

License

Commercial or Open Source

commercial

limited edition free

commercial

restricted free version is available

commercial

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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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, Clojure

C++

Java

Server operating systems

All OS with a Java VM

Linux
Windows

Linux
macOS
Windows

Linux
macOS

for devlopment

Data scheme

yes

RDF schemas

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

depending on connected data-source

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

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

RESTful HTTP API
SPARQL 1.1

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

Clojure
Java

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

C
Java

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

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

yes, depending on connected data-source

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

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

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes, but depending on the SQL-Server Edition

replication via a shared file system

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

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

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

recommended only for testing and development

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Roles, resources, and access types

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...
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Competitive advantages

High performance analtyics and data processing of very large data sets Powerful ANSI...
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Typical application scenarios

Performant analytics query engine for data warehouses, data lakes, and data lakehouses...
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Key customers

Trino is widely adopted across the globe as freely-available open source software....
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Market metrics

33000+ commits in GitHub 8200+ stargazers in GitHub 1200+ pull requests merged in...
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Licensing and pricing models

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

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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.