DBMS > Atos Standard Common Repository vs. Badger vs. Faircom EDGE

System Properties Comparison Atos Standard Common Repository vs. Badger vs. Faircom EDGE

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Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

Primary database model

Document store
Key-value store

Key-value store

Key-value store
Relational DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

github.com/dgraph-io/badger

www.faircom.com/products/faircom-edge

Technical documentation

godoc.org/github.com/dgraph-io/badger

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

Developer

Atos Convergence Creators

DGraph Labs

FairCom Corporation

Initial release

2016

2017

1979

Current release

1703

V3, October 2020

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Restricted, free version available

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

Java

ANSI C, C++

Server operating systems

Linux

BSD
Linux
OS X
Solaris
Windows

Android
Linux

ARM, x86
Raspbian
Windows

Data scheme

Schema and schema-less with LDAP views

schema-free

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

Typing

predefined data types such as float or date

optional

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

LDAP

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

Supported programming languages

All languages with LDAP bindings

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

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

File partitioning

Customizable business rules for partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

Synchronous and asynchronous realtime replication based on transaction logs

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

none

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

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

LDAP bind authentication

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

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