DBMS > Apache Pinot vs. EventStoreDB vs. Faircom EDGE vs. mSQL

System Properties Comparison Apache Pinot vs. EventStoreDB vs. Faircom EDGE vs. mSQL

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Editorial information provided by DB-Engines

Name

Description

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

Industrial-strength, open-source database solution built from the ground up for event sourcing.

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

mSQL (Mini SQL) is a simple and lightweight RDBMS

Primary database model

Relational DBMS

Event Store

Key-value store
Relational DBMS

Relational DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.35
Rank	#274	Overall
	#128	Relational DBMS

Score	1.07
Rank	#181	Overall
	#1	Event Stores

Score	0.02
Rank	#370	Overall
	#55	Key-value stores
	#157	Relational DBMS

Score	1.26
Rank	#163	Overall
	#74	Relational DBMS

Website

pinot.apache.org

www.eventstore.com

www.faircom.com/products/faircom-edge

hughestech.com.au/products/msql

Technical documentation

docs.pinot.apache.org

developers.eventstore.com

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

Developer

Apache Software Foundation and contributors

Event Store Limited

FairCom Corporation

Hughes Technologies

Initial release

2015

2012

1979

1994

Current release

1.0.0, September 2023

21.2, February 2021

V3, October 2020

4.4, October 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

commercial

Restricted, free version available

commercial

free licenses can be provided

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

ANSI C, C++

Server operating systems

All OS with a Java JDK11 or higher

Linux
Windows

Android
Linux

ARM, x86
Raspbian
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

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

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

SQL

Support of SQL

SQL-like query language

yes

ANSI SQL queries

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

JDBC

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

JDBC
ODBC

Supported programming languages

Go
Java
Python

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

C
C++
Delphi
Java
Perl
PHP
Tcl

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

File partitioning

Customizable business rules for partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

none

Foreign keys

Referential integrity

yes

when using SQL

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

Durability

Support for making data persistent

yes

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.

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