DBMS > Faircom EDGE vs. FoundationDB vs. Hive

System Properties Comparison Faircom EDGE vs. FoundationDB vs. Hive

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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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Primary database model

Key-value store
Relational DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

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	1.03
Rank	#190	Overall
	#31	Document stores
	#28	Key-value stores
	#89	Relational DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Website

www.faircom.com/products/faircom-edge

github.com/apple/foundationdb

hive.apache.org

Technical documentation

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

apple.github.io/foundationdb

cwiki.apache.org/confluence/display/Hive/Home

Developer

FairCom Corporation

FoundationDB

Apache Software Foundation

initially developed by Facebook

Initial release

1979

2013

2012

Current release

V3, October 2020

6.2.28, November 2020

3.1.3, April 2022

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache 2.0

Open Source

Apache Version 2

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

ANSI C, C++

C++

Java

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

Linux
OS X
Windows

All OS with a Java VM

Data scheme

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

schema-free

some layers support schemas

yes

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

some layers support typing

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

yes

ANSI SQL queries

supported in specific SQL layer only

SQL-like DML and DDL statements

APIs and other access methods

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

JDBC
ODBC
Thrift

Supported programming languages

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

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

in SQL-layer only

yes

user defined functions and integration of map-reduce

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

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

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

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.

Access rights for users, groups and roles

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More resources

DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

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