DBMS > Atos Standard Common Repository vs. Faircom EDGE vs. LeanXcale vs. Newts vs. SiriDB

System Properties Comparison Atos Standard Common Repository vs. Faircom EDGE vs. LeanXcale vs. Newts vs. SiriDB

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

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

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Time Series DBMS based on Cassandra

Open Source Time Series DBMS

Primary database model

Document store
Key-value store

Key-value store
Relational DBMS

Time Series DBMS

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

Score	0.09
Rank	#362	Overall
	#53	Key-value stores
	#155	Relational DBMS

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Website

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

www.faircom.com/products/faircom-edge

www.leanxcale.com

opennms.github.io/newts

siridb.com

Technical documentation

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

github.com/OpenNMS/newts/wiki

docs.siridb.com

Developer

Atos Convergence Creators

FairCom Corporation

LeanXcale

OpenNMS Group

Cesbit

Initial release

2016

1979

2015

2014

2017

Current release

1703

V3, October 2020

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

Apache 2.0

Open Source

MIT License

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

Server operating systems

Linux

Android
Linux

ARM, x86
Raspbian
Windows

Linux
OS X
Windows

Linux

Data scheme

Schema and schema-less with LDAP views

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

yes

schema-free

yes

Typing

predefined data types such as float or date

optional

yes, ANSI Standard SQL Types

yes

Numeric data

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

yes

through Apache Derby

APIs and other access methods

LDAP

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

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

HTTP REST
Java API

HTTP API

Supported programming languages

All languages with LDAP bindings

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

C
Java
Scala

Java

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

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

File partitioning

Customizable business rules for partitioning

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

selectable replication factor

based on Cassandra

yes

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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.

simple rights management via user accounts

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