DBMS > Faircom EDGE vs. FatDB vs. Microsoft Azure Table Storage vs. XTDB

System Properties Comparison Faircom EDGE vs. FatDB vs. Microsoft Azure Table Storage vs. XTDB

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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.

A Wide Column Store for rapid development using massive semi-structured datasets

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Key-value store
Relational DBMS

Document store
Key-value store

Wide column store

Document 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	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

www.faircom.com/products/faircom-edge

azure.microsoft.com/en-us/services/storage/tables

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

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

www.xtdb.com/docs

Developer

FairCom Corporation

FatCloud

Microsoft

Juxt Ltd.

Initial release

1979

2012

2019

Current release

V3, October 2020

1.19, September 2021

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

ANSI C, C++

Clojure

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

Windows

hosted

All OS with a Java 8 (and higher) VM
Linux

Data scheme

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

schema-free

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

yes

yes, extensible-data-notation format

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

yes

ANSI SQL queries

Via inetgration in SQL Server

limited SQL, making use of Apache Calcite

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

RESTful HTTP API

HTTP REST
JDBC

Supported programming languages

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

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Clojure
Java

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

via applications

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

selectable replication factor

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes, each node contains all data

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

Foreign keys

Referential integrity

yes

when using SQL

Transaction concepts

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

ACID

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

Access rights based on private key authentication or shared access signatures

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