DBMS > Faircom EDGE vs. FatDB vs. FileMaker vs. KeyDB vs. OushuDB

System Properties Comparison Faircom EDGE vs. FatDB vs. FileMaker vs. KeyDB vs. OushuDB

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.

FileMaker is a cross-platform RDBMS that includes a GUI frontend.

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

Primary database model

Key-value store
Relational DBMS

Document store
Key-value store

Relational DBMS

Key-value store

Relational 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	48.20
Rank	#20	Overall
	#14	Relational DBMS

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Score	0.04
Rank	#363	Overall
	#154	Relational DBMS

Website

www.faircom.com/products/faircom-edge

www.claris.com/filemaker

github.com/Snapchat/KeyDB
keydb.dev

www.oushu.com/product/oushuDB

Technical documentation

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

www.claris.com/resources/documentation

docs.keydb.dev

www.oushu.com/documentation

Developer

FairCom Corporation

FatCloud

Claris

a subsidiary of Apple

EQ Alpha Technology Ltd.

Oushu

Initial release

1979

2012

1983

2019

Current release

V3, October 2020

19.4.1, November 2021

4.0.1, August 2020

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

BSD-3

commercial

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++

C++

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

Windows

iOS

client part only
Linux
OS X
Windows

Linux

Data scheme

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

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

A http query request can return the data in XML format

Secondary indexes

yes

by using the Redis Search module

yes

SQL

Support of SQL

yes

ANSI SQL queries

Via inetgration in SQL Server

yes

via plugins

Full-featured ANSI SQL support

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

Filemaker WebDirect
JDBC
ODBC

Proprietary protocol

RESP - REdis Serialization Protoco

JDBC
ODBC

Supported programming languages

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

PHP

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

C
C++

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

via applications

yes

Lua

yes

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

Sharding

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

selectable replication factor

Source-replica replication, warm standby

since Version 14

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Foreign keys

Referential integrity

yes

when using SQL

yes

Transaction concepts

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

ACID

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

simple rights management via user accounts and connection to external directory services

simple password-based access control and ACL

Kerberos, SSL and role based access

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