DBMS > Atos Standard Common Repository vs. Hawkular Metrics vs. Microsoft Azure Table Storage vs. OrigoDB

System Properties Comparison Atos Standard Common Repository vs. Hawkular Metrics vs. Microsoft Azure Table Storage vs. OrigoDB

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Editorial information provided by DB-Engines
Name	Atos Standard Common Repository  Xexclude from comparison	Hawkular Metrics  Xexclude from comparison	Microsoft Azure Table Storage  Xexclude from comparison	OrigoDB  Xexclude from comparison
	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	Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.	A Wide Column Store for rapid development using massive semi-structured datasets	A fully ACID in-memory object graph database
Primary database model	Document store Key-value store	Time Series DBMS	Wide column store	Document store Object oriented DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart		Score 0.00 Rank #379   Overall #40   Time Series DBMS	Score 4.48 Rank #75   Overall #6   Wide column stores	Score 0.00 Rank #383   Overall #53   Document stores #20   Object oriented DBMS
Website	atos.net/en/convergence-creators/portfolio/standard-common-repository	www.hawkular.org	azure.microsoft.com/­en-us/­services/­storage/­tables	origodb.com
Technical documentation		www.hawkular.org/­hawkular-metrics/­docs/­user-guide		origodb.com/­docs
Developer	Atos Convergence Creators	Community supported by Red Hat	Microsoft	Robert Friberg et al
Initial release	2016	2014	2012	2009 under the name LiveDB
Current release	1703
License Commercial or Open Source	commercial	Open Source Apache 2.0	commercial	Open Source
Cloud-based only Only available as a cloud service	no	no	yes	no
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed.
Implementation language	Java	Java		C#
Server operating systems	Linux	Linux OS X Windows	hosted	Linux Windows
Data scheme	Schema and schema-less with LDAP views	schema-free	schema-free	yes
Typing predefined data types such as float or date	optional	yes	yes	User defined using .NET types and collections
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	no	no	no can be achieved using .NET
Secondary indexes	yes	no	no	yes
SQL Support of SQL	no	no	no	no
APIs and other access methods	LDAP	HTTP REST	RESTful HTTP API	.NET Client API HTTP API LINQ
Supported programming languages	All languages with LDAP bindings	Go Java Python Ruby	.Net C# C++ Java JavaScript (Node.js) PHP Python Ruby	.Net
Server-side scripts Stored procedures	no	no	no	yes
Triggers	yes	yes via Hawkular Alerting	no	yes Domain Events
Partitioning methods Methods for storing different data on different nodes	Sharding cell division	Sharding based on Cassandra	Sharding Implicit feature of the cloud service	horizontal partitioning client side managed; servers are not synchronized
Replication methods Methods for redundantly storing data on multiple nodes	yes	selectable replication factor based on Cassandra	yes implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.	Source-replica replication
MapReduce Offers an API for user-defined Map/Reduce methods		no	no	no
Consistency concepts Methods to ensure consistency in a distributed system	Immediate Consistency or Eventual Consistency depending on configuration	Eventual Consistency based on Cassandra Immediate Consistency based on Cassandra	Immediate Consistency
Foreign keys Referential integrity	no	no	no	depending on model
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	Atomic execution of specific operations	no	optimistic locking	ACID
Concurrency Support for concurrent manipulation of data	yes	yes	yes	yes
Durability Support for making data persistent	yes	yes	yes	yes Write ahead log
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.	yes	no	no	yes
User concepts Access control	LDAP bind authentication	no	Access rights based on private key authentication or shared access signatures	Role based authorization
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More resources
	Atos Standard Common Repository	Hawkular Metrics	Microsoft Azure Table Storage	OrigoDB
Recent citations in the news	Infographic: What makes a Mobile Operator's setup future proof? 10 February 2024, Atos provided by Google News	Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived… • DEVCLASS 5 June 2019, DevClass provided by Google News	Working with Azure to Use and Manage Data Lakes 7 March 2024, Simplilearn How to use Azure Table storage in .Net 14 January 2019, InfoWorld How to Use C# Azure.Data.Tables SDK with Azure Cosmos DB 9 July 2021, hackernoon.com Inside Azure File Storage 7 October 2015, Microsoft How to write data to Azure Table Store with an Azure Function 14 April 2017, Experts Exchange provided by Google News

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