DBMS > Faircom EDGE vs. RocksDB

System Properties Comparison Faircom EDGE vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Key-value store
Relational DBMS

Key-value store

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Trend Chart

Score	0.00
Rank	#402	Overall
	#65	Key-value stores
	#164	Relational DBMS

Score	3.92
Rank	#94	Overall
	#15	Key-value stores

Website

www.faircom.com/products/faircomedge-iot-database

rocksdb.org

Technical documentation

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

github.com/facebook/rocksdb/wiki

Developer

FairCom Corporation

Facebook, Inc.

Initial release

1979

2013

Current release

V3, October 2020

7.10.2, March 2023

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

BSD

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++

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

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

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

APIs and other access methods

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

C++ API
Java API

Supported programming languages

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

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

Foreign keys

Referential integrity

yes

when using SQL

Transaction concepts

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

ACID

yes

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.

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