DBMS > Atos Standard Common Repository vs. Geode vs. Google Cloud Datastore vs. Microsoft Azure Cosmos DB

System Properties Comparison Atos Standard Common Repository vs. Geode vs. Google Cloud Datastore 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

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

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Document store
Key-value store

Key-value store

Document 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	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	27.71
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

geode.apache.org

cloud.google.com/datastore

azure.microsoft.com/services/cosmos-db

Technical documentation

geode.apache.org/docs

cloud.google.com/datastore/docs

learn.microsoft.com/azure/cosmos-db

Developer

Atos Convergence Creators

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

Google

Microsoft

Initial release

2016

2002

2008

2014

Current release

1703

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

Server operating systems

Linux

All OS with a Java VM

the JDK (8 or later) is also required

hosted

Data scheme

Schema and schema-less with LDAP views

schema-free

Typing

predefined data types such as float or date

optional

yes

yes, details here

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

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

SQL-like query language (OQL)

SQL-like query language (GQL)

SQL-like query language

APIs and other access methods

LDAP

Java Client API
Memcached protocol
RESTful HTTP API

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

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

Supported programming languages

All languages with LDAP bindings

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

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

user defined functions

using Google App Engine

JavaScript

Triggers

yes

Cache Event Listeners

Callbacks using the Google Apps Engine

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

Multi-source replication using Paxos

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

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

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

Transaction concepts

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

Atomic execution of specific operations

yes, on a single node

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

Multi-item ACID transactions with snapshot isolation within a partition

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

Access rights per client and object definable

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Access rights can be defined down to the item level

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