DBMS > Faircom EDGE vs. HyperSQL vs. MySQL vs. Prometheus vs. Trino

System Properties Comparison Faircom EDGE vs. HyperSQL vs. MySQL vs. Prometheus vs. Trino

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Widely used open source RDBMS

Open-source Time Series DBMS and monitoring system

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

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Relational DBMS

Secondary database models

Document store
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	0.09
Rank	#362	Overall
	#53	Key-value stores
	#155	Relational DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	4.99
Rank	#65	Overall
	#36	Relational DBMS

Website

www.faircom.com/products/faircom-edge

Technical documentation

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

hsqldb.org/web/hsqlDocsFrame.html

dev.mysql.com/doc

prometheus.io/docs

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

Social network pages

Developer

FairCom Corporation

Oracle

since 2010, originally MySQL AB, then Sun

Trino Software Foundation

Initial release

1979

2001

1995

2015

2012

2020 rebranded from PrestoSQL

Current release

V3, October 2020

2.7.2, June 2023

8.4.0, April 2024

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

based on BSD license

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache 2.0

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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Implementation language

ANSI C, C++

Java

C and C++

Java

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

All OS with a Java VM

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

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

Linux
macOS

for devlopment

Data scheme

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

yes

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

yes

Numeric data only

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

Import of XML data possible

Secondary indexes

yes

depending on connected data-source

SQL

Support of SQL

yes

ANSI SQL queries

yes

with proprietary extensions

yes

APIs and other access methods

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

HTTP API

JDBC via HTTP
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

RESTful HTTP/JSON API

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

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

All languages supporting JDBC/ODBC
Java

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

Java, SQL

yes

proprietary syntax

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

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

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

none

Multi-source replication
Source-replica replication

yes

by Federation

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

none

depending on connected data-source

Foreign keys

Referential integrity

yes

when using SQL

yes

not for MyISAM storage engine

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

not for MyISAM storage engine

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

table locks or row locks depending on storage engine

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.

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

SQL standard access control

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Key customers

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Market metrics

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