DBMS > Faircom EDGE vs. FoundationDB vs. OrigoDB vs. Riak KV

System Properties Comparison Faircom EDGE vs. FoundationDB vs. OrigoDB vs. Riak KV

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Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in 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

Ordered key-value store. Core features are complimented by layers.

A fully ACID in-memory object graph database

Distributed, fault tolerant key-value store

Primary database model

Key-value store
Relational DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Document store
Object oriented DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

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	1.06
Rank	#185	Overall
	#31	Document stores
	#28	Key-value stores
	#85	Relational DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Website

www.faircom.com/products/faircom-edge

github.com/apple/foundationdb

origodb.com

Technical documentation

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

apple.github.io/foundationdb

origodb.com/docs

www.tiot.jp/riak-docs/riak/kv/latest

Developer

FairCom Corporation

FoundationDB

Robert Friberg et al

OpenSource, formerly Basho Technologies

Initial release

1979

2013

2009

under the name LiveDB

2009

Current release

V3, October 2020

6.2.28, November 2020

3.2.0, December 2022

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache 2.0

Open Source

Apache version 2, commercial enterprise edition

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++

Erlang

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

Linux
OS X
Windows

Linux
Windows

Linux
OS X

Data scheme

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

schema-free

some layers support schemas

yes

schema-free

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

some layers support typing

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

restricted

SQL

Support of SQL

yes

ANSI SQL queries

supported in specific SQL layer only

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
HTTP API
LINQ

HTTP API
Native Erlang Interface

Supported programming languages

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

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

.Net

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

in SQL-layer only

yes

Erlang

Triggers

yes

Domain Events

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes

Source-replica replication

selectable replication factor

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

Linearizable consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

when using SQL

in SQL-layer only

depending on model

links between data sets can be stored

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

yes

Durability

Support for making data persistent

yes

Write ahead log

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.

Role based authorization

yes, using Riak Security

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