DBMS > Faircom EDGE vs. RDFox vs. SQLite vs. Trino

System Properties Comparison Faircom EDGE vs. RDFox vs. SQLite vs. Trino

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Editorial information provided by DB-Engines

Name

Description

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

High performance knowledge graph and semantic reasoning engine

Widely used embeddable, in-process RDBMS

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

Primary database model

Key-value store
Relational DBMS

Graph DBMS
RDF store

Relational DBMS

Secondary database models

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	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

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

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	5.00
Rank	#66	Overall
	#36	Relational DBMS

Website

www.faircom.com/products/faircom-edge

www.oxfordsemantic.tech

www.sqlite.org

trino.io

Technical documentation

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

docs.oxfordsemantic.tech

www.sqlite.org/docs.html

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

Social network pages

Developer

FairCom Corporation

Oxford Semantic Technologies

Dwayne Richard Hipp

Trino Software Foundation

Initial release

1979

2017

2000

2012

2020 rebranded from PrestoSQL

Current release

V3, October 2020

6.0, Septermber 2022

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

Public Domain

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

ANSI C, C++

C++

Java

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

Linux
macOS
Windows

server-less

Linux
macOS

for devlopment

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

yes

RDF schemas

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

yes

not rigid because of 'dynamic typing' concept.

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

ANSI SQL queries

yes

SQL-92 is not fully supported

yes

APIs and other access methods

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

RESTful HTTP API
SPARQL 1.1

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

C
Java

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes, depending on connected data-source

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

none

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

replication via a shared file system

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
Tunable Consistency

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

depending on connected data-source

Foreign keys

Referential integrity

yes

when using SQL

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

across SQL and NoSQL

yes

via file-system locks

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 user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

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

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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

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