DBMS > Atos Standard Common Repository vs. Faircom EDGE vs. GBase vs. InterSystems Caché

System Properties Comparison Atos Standard Common Repository vs. Faircom EDGE vs. GBase vs. InterSystems Caché

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

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

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

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

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

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

A multi-model DBMS and application server

Primary database model

Document store
Key-value store

Key-value store
Relational DBMS

Relational DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Secondary database models

Document store

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	1.07
Rank	#185	Overall
	#86	Relational DBMS

Website

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

www.faircom.com/products/faircom-edge

www.gbase.cn

www.intersystems.com/products/cache

Technical documentation

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

docs.intersystems.com

Developer

Atos Convergence Creators

FairCom Corporation

General Data Technology Co., Ltd.

InterSystems

Initial release

2016

1979

2004

1997

Current release

1703

V3, October 2020

GBase 8a, GBase 8s, GBase 8c

2018.1.4, May 2020

License

Commercial or Open Source

commercial

Restricted, free version available

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

Java

ANSI C, C++

C, Java, Python

Server operating systems

Linux

Android
Linux

ARM, x86
Raspbian
Windows

Linux

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

Schema and schema-less with LDAP views

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

yes

depending on used data model

Typing

predefined data types such as float or date

optional

yes, ANSI Standard SQL Types

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

Standard with numerous extensions

yes

APIs and other access methods

LDAP

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

ADO.NET
C API
JDBC
ODBC

.NET Client API
JDBC
ODBC
RESTful HTTP API

Supported programming languages

All languages with LDAP bindings

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

C#
C++
Java

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

File partitioning

Customizable business rules for partitioning

horizontal partitioning (by range, list and hash) and vertical partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes

Source-replica replication

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

Immediate Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

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

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

LDAP bind authentication

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

yes

Access rights for users, groups and roles

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

FairCom kicks off new era of database technology USA - English
10 November 2020, PR Newswire

Winners of the 2021 IoT Evolution Product of the Year Awards Announced
6 July 2021, IoT Evolution World

Trend-Setting Products in Data and Information Management for 2023
8 December 2022, Database Trends and Applications

How To Collect, Store, and Query IoT Data With MQTT + SQL
16 June 2022, IoT For All

Trend-Setting Products in Data and Information Management for 2024
6 December 2023, Database Trends and Applications

provided by Google News

Defense Health Agency Awards Four Points Technology $39 Million for Intersystems Software Licenses and Maintenance
21 September 2023, ClearanceJobs

AWS, GCP, Oracle, Azure, SAP Lead Cloud DBMS Market: Gartner
12 February 2022, CRN

Announcing IBM Spectrum Sentinel: Building a Cyber Resilient Future
24 June 2022, IBM

Associative Data Modeling Demystified - Part1 - DataScienceCentral.com
9 July 2016, Data Science Central

Nearly three years on from Cambridge's Epic go-live
23 August 2017, Digital Health

provided by Google News

Share this page