DBMS > Atos Standard Common Repository vs. Hazelcast vs. Oracle Rdb vs. Yaacomo

System Properties Comparison Atos Standard Common Repository vs. Hazelcast vs. Oracle Rdb vs. Yaacomo

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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.

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

A widely adopted in-memory data grid

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Document store
Key-value store

Key-value store

Relational DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

DB-Engines Ranking measures the popularity of database management systems
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Score	6.87
Rank	#55	Overall
	#6	Key-value stores

Score	1.08
Rank	#187	Overall
	#85	Relational DBMS

Website

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

hazelcast.com

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

yaacomo.com

Technical documentation

hazelcast.org/imdg/docs

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

Developer

Atos Convergence Creators

Hazelcast

Oracle, originally developed by Digital Equipment Corporation (DEC)

Q2WEB GmbH

Initial release

2016

2008

1984

2009

Current release

1703

5.3.6, November 2023

7.4.1.1, 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

commercial

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

Linux

All OS with a Java VM

HP Open VMS

Android
Linux
Windows

Data scheme

Schema and schema-less with LDAP views

schema-free

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

yes

Typing

predefined data types such as float or date

optional

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

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

LDAP

JCache
JPA
Memcached protocol
RESTful HTTP API

JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

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

one or two-phase-commit; repeatable reads; read commited

yes, on a single node

ACID

Concurrency

Support for concurrent manipulation of data

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

LDAP bind authentication

Role-based access control

fine grained access rights according to SQL-standard

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