DBMS > Atos Standard Common Repository vs. Faircom DB vs. JanusGraph vs. Microsoft Access

System Properties Comparison Atos Standard Common Repository vs. Faircom DB vs. JanusGraph vs. Microsoft Access

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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

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Primary database model

Document store
Key-value store

Key-value store
Relational DBMS

Graph DBMS

Relational DBMS

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

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Website

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

www.faircom.com/products/faircom-db

janusgraph.org

www.microsoft.com/en-us/microsoft-365/access

Technical documentation

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

docs.janusgraph.org

developer.microsoft.com/en-us/access

Developer

Atos Convergence Creators

FairCom Corporation

Linux Foundation; originally developed as Titan by Aurelius

Microsoft

Initial release

2016

1979

2017

1992

Current release

1703

V12, November 2020

0.6.3, February 2023

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache 2.0

commercial

Bundled with Microsoft Office

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++

Java

C++

Server operating systems

Linux

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Linux
OS X
Unix
Windows

Windows

Not a real database server, but making use of DLLs

Data scheme

Schema and schema-less with LDAP views

schema free, schema optional, schema required, partial schema,

yes

Typing

predefined data types such as float or date

optional

yes, ANSI SQL Types, JSON, typed binary structures

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 with proprietary extensions

yes

but not compliant to any SQL standard

APIs and other access methods

LDAP

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ADO.NET
DAO
ODBC
OLE DB

Supported programming languages

All languages with LDAP bindings

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

Clojure
Java
Python

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

since Access 2010 using the ACE-engine

Triggers

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

Atomic execution of specific operations

tunable from ACID to Eventually Consistent

ACID

but no files for transaction logging

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Yes, tunable from durable to delayed durability to in-memory

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

but no files for transaction logging

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 access rights according to SQL-standard with additional protections for files

User authentification and security via Rexster Graph Server

a simple user-level security was built in till version Access 2003

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More resources

DB-Engines blog posts

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3 October 2012, Matthias Gelbmann, Paul Andlinger

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