DBMS > Atos Standard Common Repository vs. eXtremeDB vs. Google Cloud Spanner vs. Microsoft Azure Table Storage

System Properties Comparison Atos Standard Common Repository vs. eXtremeDB vs. Google Cloud Spanner vs. Microsoft Azure Table Storage

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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

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

A Wide Column Store for rapid development using massive semi-structured datasets

Primary database model

Document store
Key-value store

Relational DBMS
Time Series DBMS

Relational DBMS

Wide column store

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	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Website

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

www.mcobject.com

cloud.google.com/spanner

azure.microsoft.com/en-us/services/storage/tables

Technical documentation

www.mcobject.com/docs/extremedb.htm

cloud.google.com/spanner/docs

Developer

Atos Convergence Creators

McObject

Google

Microsoft

Initial release

2016

2001

2017

2012

Current release

1703

8.2, 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

C and C++

Server operating systems

Linux

AIX
HP-UX
Linux
macOS
Solaris
Windows

hosted

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

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

support of XML interfaces available

Secondary indexes

yes

SQL

Support of SQL

yes

with the option: eXtremeSQL

yes

Query statements complying to ANSI 2011

APIs and other access methods

LDAP

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

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

RESTful HTTP API

Supported programming languages

All languages with LDAP bindings

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

Go
Java
JavaScript (Node.js)
Python

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

by defining events

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 with 3 replicas for regional instances.

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

Transaction concepts

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

Atomic execution of specific operations

ACID

Strict serializable isolation

optimistic locking

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

Access rights based on private key authentication or shared access signatures

More information provided by the system vendor

Specific characteristics

eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more

Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more

Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more

Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more

Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
» more

Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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