DBMS > 4D vs. Atos Standard Common Repository vs. Blueflood vs. InfinityDB vs. RDF4J

System Properties Comparison 4D vs. Atos Standard Common Repository vs. Blueflood vs. InfinityDB vs. RDF4J

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

Scalable TimeSeries DBMS based on Cassandra

A Java embedded Key-Value Store which extends the Java Map interface

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Relational DBMS

Document store
Key-value store

Time Series DBMS

Key-value store

RDF store

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

Score	2.68
Rank	#110	Overall
	#54	Relational DBMS

Score	0.09
Rank	#353	Overall
	#33	Time Series DBMS

Score	0.07
Rank	#359	Overall
	#54	Key-value stores

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Website

www.4d.com

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

blueflood.io

boilerbay.com

rdf4j.org

Technical documentation

developer.4d.com

github.com/rax-maas/blueflood/wiki

boilerbay.com/infinitydb/manual

rdf4j.org/documentation

Developer

4D, Inc

Atos Convergence Creators

Rackspace

Boiler Bay Inc.

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

1984

2016

2013

2002

2004

Current release

v20, April 2023

1703

4.0

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

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

Server operating systems

OS X
Windows

Linux

Linux
OS X

All OS with a Java VM

Linux
OS X
Unix
Windows

Data scheme

yes

Schema and schema-less with LDAP views

predefined scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

optional

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

yes

close to SQL 92

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

LDAP

HTTP REST

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

4D proprietary IDE
PHP

All languages with LDAP bindings

Java

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

cell division

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

selectable replication factor

based on Cassandra

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

READ-COMMITTED or SERIALIZED

Foreign keys

Referential integrity

yes

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

Optimistic locking for transactions; no isolation for bulk loads

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

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