DBMS > Atos Standard Common Repository vs. Oracle Coherence vs. Oracle Rdb vs. Pinecone

System Properties Comparison Atos Standard Common Repository vs. Oracle Coherence vs. Oracle Rdb vs. Pinecone

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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

Oracles in-memory data grid solution

A managed, cloud-native vector database

Primary database model

Document store
Key-value store

Key-value store

Relational DBMS

Vector DBMS

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

Score	1.90
Rank	#127	Overall
	#21	Key-value stores

Score	1.04
Rank	#184	Overall
	#84	Relational DBMS

Score	3.02
Rank	#87	Overall
	#3	Vector DBMS

Website

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

www.oracle.com/java/coherence

www.oracle.com/database/technologies/related/rdb.html

www.pinecone.io

Technical documentation

docs.oracle.com/en/middleware/standalone/coherence

www.oracle.com/database/technologies/related/rdb-doc.html

docs.pinecone.io/docs/overview

Developer

Atos Convergence Creators

Oracle

Oracle, originally developed by Digital Equipment Corporation (DEC)

Pinecone Systems, Inc

Initial release

2016

2007

1984

2019

Current release

1703

14.1, August 2023

7.4.1.1, 2021

License

Commercial or Open Source

commercial

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

Server operating systems

Linux

All OS with a Java VM

HP Open VMS

hosted

Data scheme

Schema and schema-less with LDAP views

schema-free

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

Typing

predefined data types such as float or date

optional

yes

String, Number, Boolean

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

APIs and other access methods

LDAP

JCache
JPA
RESTful HTTP API

RESTful HTTP API

Supported programming languages

All languages with LDAP bindings

.Net
C++
Java

Python

Server-side scripts

Stored procedures

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, with selectable consistency level

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
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

configurable

yes, on a single node

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

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

authentification to access the cache via certificates or http basic authentication

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