DBMS > Atos Standard Common Repository vs. Hazelcast vs. SpatiaLite

System Properties Comparison Atos Standard Common Repository vs. Hazelcast vs. SpatiaLite

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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 widely adopted in-memory data grid

Spatial extension of SQLite

Primary database model

Document store
Key-value store

Key-value store

Spatial DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

Relational DBMS

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Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Website

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

hazelcast.com

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

hazelcast.org/imdg/docs

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Atos Convergence Creators

Hazelcast

Alessandro Furieri

Initial release

2016

2008

Current release

1703

5.3.6, November 2023

5.0.0, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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++

Server operating systems

Linux

All OS with a Java VM

server-less

Data scheme

Schema and schema-less with LDAP views

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

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

none

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

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

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

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More resources

DB-Engines blog posts

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