DBMS > Atos Standard Common Repository vs. Pinecone vs. RDF4J vs. SwayDB

System Properties Comparison Atos Standard Common Repository vs. Pinecone vs. RDF4J vs. SwayDB

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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 managed, cloud-native vector database

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Document store
Key-value store

Vector DBMS

RDF store

Key-value store

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

Score	3.16
Rank	#95	Overall
	#2	Vector DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

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

www.pinecone.io

rdf4j.org

swaydb.simer.au

Technical documentation

docs.pinecone.io/docs/overview

rdf4j.org/documentation

Developer

Atos Convergence Creators

Pinecone Systems, Inc

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

Simer Plaha

Initial release

2016

2019

2004

2018

Current release

1703

License

Commercial or Open Source

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

GNU Affero GPL V3.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Scala

Server operating systems

Linux

hosted

Linux
OS X
Unix
Windows

Data scheme

Schema and schema-less with LDAP views

yes

RDF Schemas

schema-free

Typing

predefined data types such as float or date

optional

String, Number, Boolean

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

RESTful HTTP API

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

Python

Java
PHP
Python

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

Triggers

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

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

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of specific operations

ACID

Isolation support depends on the API used

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

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