DBMS > Atos Standard Common Repository vs. Dragonfly vs. RDF4J

System Properties Comparison Atos Standard Common Repository vs. Dragonfly vs. RDF4J

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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

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

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

Primary database model

Document store
Key-value store

Key-value store

RDF store

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

Score	0.41
Rank	#266	Overall
	#38	Key-value stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

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

github.com/dragonflydb/dragonfly
www.dragonflydb.io

rdf4j.org

Technical documentation

www.dragonflydb.io/docs

rdf4j.org/documentation

Developer

Atos Convergence Creators

DragonflyDB team and community contributors

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

Initial release

2016

2023

2004

Current release

1703

1.0, March 2023

License

Commercial or Open Source

commercial

Open Source

BSL 1.1

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

C++

Java

Server operating systems

Linux

Linux
OS X
Unix
Windows

Data scheme

Schema and schema-less with LDAP views

scheme-free

yes

RDF Schemas

Typing

predefined data types such as float or date

optional

strings, hashes, lists, sets, sorted sets, bit 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

SQL

Support of SQL

APIs and other access methods

LDAP

Proprietary protocol

RESP - REdis Serialization Protocol

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

All languages with LDAP bindings

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

Java
PHP
Python

Server-side scripts

Stored procedures

Lua

yes

Triggers

yes

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

none

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

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of specific operations

Atomic execution of command blocks and scripts

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

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

LDAP bind authentication

Password-based authentication

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