DBMS > Faircom EDGE vs. FatDB vs. Postgres-XL vs. SiteWhere vs. Vitess

System Properties Comparison Faircom EDGE vs. FatDB vs. Postgres-XL vs. SiteWhere vs. Vitess

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

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

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

M2M integration platform for persisting/querying time series data

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Key-value store
Relational DBMS

Document store
Key-value store

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

www.faircom.com/products/faircom-edge

www.postgres-xl.org

github.com/sitewhere/sitewhere

vitess.io

Technical documentation

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

www.postgres-xl.org/documentation

sitewhere1.sitewhere.io/index.html

vitess.io/docs

Developer

FairCom Corporation

FatCloud

SiteWhere

The Linux Foundation, PlanetScale

Initial release

1979

2012

2014

since 2012, originally named StormDB

2010

2013

Current release

V3, October 2020

10 R1, October 2018

15.0.2, December 2022

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

Mozilla public license

Open Source

Common Public Attribution License Version 1.0

Open Source

Apache Version 2.0, commercial licenses available

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.

Implementation language

ANSI C, C++

Java

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

Windows

Linux
macOS

Linux
OS X
Windows

Docker
Linux
macOS

Data scheme

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

schema-free

yes

predefined scheme

yes

Typing

predefined data types such as float or date

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

ANSI SQL queries

Via inetgration in SQL Server

yes

distributed, parallel query execution

yes

with proprietary extensions

APIs and other access methods

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

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP REST

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

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

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

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

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

via applications

user defined functions

yes

proprietary syntax

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

Sharding

horizontal partitioning

Sharding

based on HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

selectable replication factor

based on HBase

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

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

MVCC

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

table locks or row locks depending on storage engine

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.

Can implement custom security layer via applications

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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