DBMS > Atos Standard Common Repository vs. eXtremeDB vs. Geode vs. Microsoft Azure Cosmos DB

System Properties Comparison Atos Standard Common Repository vs. eXtremeDB vs. Geode vs. Microsoft Azure Cosmos DB

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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

Natively in-memory DBMS with options for persistency, high-availability and clustering

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Document store
Key-value store

Relational DBMS
Time Series DBMS

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

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

Score	0.74
Rank	#223	Overall
	#103	Relational DBMS
	#18	Time Series DBMS

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

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

www.mcobject.com

geode.apache.org

azure.microsoft.com/services/cosmos-db

Technical documentation

www.mcobject.com/docs/extremedb.htm

geode.apache.org/docs

learn.microsoft.com/azure/cosmos-db

Developer

Atos Convergence Creators

McObject

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Microsoft

Initial release

2016

2001

2002

2014

Current release

1703

8.2, 2021

1.1, February 2017

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available as Gemfire

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

C and C++

Java

Server operating systems

Linux

AIX
HP-UX
Linux
macOS
Solaris
Windows

All OS with a Java VM

the JDK (8 or later) is also required

hosted

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

Typing

predefined data types such as float or date

optional

yes

JSON types

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

support of XML interfaces available

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

yes

with the option: eXtremeSQL

SQL-like query language (OQL)

SQL-like query language

APIs and other access methods

LDAP

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

Java Client API
Memcached protocol
RESTful HTTP API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Supported programming languages

All languages with LDAP bindings

.Net
C
C#
C++
Java
Lua
Python
Scala

.Net
All JVM based languages
C++
Groovy
Java
Scala

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

yes

user defined functions

JavaScript

Triggers

yes

by defining events

yes

Cache Event Listeners

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

horizontal partitioning / sharding

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

Multi-source replication

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

yes, on a single node

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

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

Access rights per client and object definable

Access rights can be defined down to the item level

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
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Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing models

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