DBMS > 4D vs. Atos Standard Common Repository vs. Faircom EDGE vs. Ignite vs. SpatiaLite

System Properties Comparison 4D vs. Atos Standard Common Repository vs. Faircom EDGE vs. Ignite vs. SpatiaLite

Editorial information provided by DB-Engines

Name

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

Description

Application development environment with integrated database management system

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

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Spatial extension of SQLite

Primary database model

Relational DBMS

Document store
Key-value store

Key-value store
Relational DBMS

Spatial DBMS

Secondary database models

Relational DBMS

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

Score	2.68
Rank	#110	Overall
	#54	Relational DBMS

Score	0.03
Rank	#380	Overall
	#59	Key-value stores
	#157	Relational DBMS

Score	3.64
Rank	#89	Overall
	#13	Key-value stores
	#48	Relational DBMS

Score	1.72
Rank	#149	Overall
	#3	Spatial DBMS

Website

www.4d.com

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

www.faircom.com/products/faircom-edge

ignite.apache.org

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

developer.4d.com

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

apacheignite.readme.io/docs

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

4D, Inc

Atos Convergence Creators

FairCom Corporation

Apache Software Foundation

Alessandro Furieri

Initial release

1984

2016

1979

2015

2008

Current release

v20, April 2023

1703

V3, October 2020

Apache Ignite 2.6

5.0.0, August 2020

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache 2.0

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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, .Net

C++

Server operating systems

OS X
Windows

Linux

Android
Linux

ARM, x86
Raspbian
Windows

Linux
OS X
Solaris
Windows

server-less

Data scheme

yes

Schema and schema-less with LDAP views

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

yes

Typing

predefined data types such as float or date

yes

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

close to SQL 92

yes

ANSI SQL queries

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

LDAP

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

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Supported programming languages

4D proprietary IDE
PHP

All languages with LDAP bindings

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

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes (compute grid and cache interceptors can be used instead)

Triggers

yes

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

cell division

File partitioning

Customizable business rules for partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes (replicated cache)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

ACID

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

Users and groups

LDAP bind authentication

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

Security Hooks for custom implementations

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