DBMS > Atos Standard Common Repository vs. FatDB vs. Microsoft Azure Data Explorer vs. OpenQM

System Properties Comparison Atos Standard Common Repository vs. FatDB vs. Microsoft Azure Data Explorer vs. OpenQM

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Editorial information provided by DB-Engines
Name	Atos Standard Common Repository  Xexclude from comparison	FatDB  Xexclude from comparison	Microsoft Azure Data Explorer  Xexclude from comparison	OpenQM also called QM  Xexclude from comparison
	This system has been discontinued and will be removed from the DB-Engines ranking.	FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
Description	Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks	A .NET NoSQL DBMS that can integrate with and extend SQL Server.	Fully managed big data interactive analytics platform	QpenQM is a high-performance, self-tuning, multi-value DBMS
Primary database model	Document store Key-value store	Document store Key-value store	Relational DBMS column oriented	Multivalue DBMS
Secondary database models			Document store If a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell Event Store this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps) Spatial DBMS Search engine support for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine Time Series DBMS see docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking measures the popularity of database management systems Trend Chart			Score 3.80 Rank #81   Overall #43   Relational DBMS	Score 0.34 Rank #284   Overall #10   Multivalue DBMS
Website	atos.net/en/convergence-creators/portfolio/standard-common-repository		azure.microsoft.com/­services/­data-explorer	www.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-open-qm
Technical documentation			docs.microsoft.com/­en-us/­azure/­data-explorer
Developer	Atos Convergence Creators	FatCloud	Microsoft	Rocket Software, originally Martin Phillips
Initial release	2016	2012	2019	1993
Current release	1703		cloud service with continuous releases	3.4-12
License Commercial or Open Source	commercial	commercial	commercial	Open Source GPLv2, extended commercial license available
Cloud-based only Only available as a cloud service	no	no	yes	no
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Implementation language	Java	C#
Server operating systems	Linux	Windows	hosted	AIX FreeBSD Linux macOS Raspberry Pi Solaris Windows
Data scheme	Schema and schema-less with LDAP views	schema-free	Fixed schema with schema-less datatypes (dynamic)	yes with some exceptions
Typing predefined data types such as float or date	optional	yes	yes bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-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		yes	yes
Secondary indexes	yes	yes	all fields are automatically indexed	yes
SQL Support of SQL	no	no Via inetgration in SQL Server	Kusto Query Language (KQL), SQL subset	no
APIs and other access methods	LDAP	.NET Client API LINQ RESTful HTTP API RPC Windows WCF Bindings	Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API
Supported programming languages	All languages with LDAP bindings	C#	.Net Go Java JavaScript (Node.js) PowerShell Python R	.Net Basic C Java Objective C PHP Python
Server-side scripts Stored procedures	no	yes via applications	Yes, possible languages: KQL, Python, R	yes
Triggers	yes	yes via applications	yes see docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy	yes
Partitioning methods Methods for storing different data on different nodes	Sharding cell division	Sharding	Sharding Implicit feature of the cloud service	yes
Replication methods Methods for redundantly storing data on multiple nodes	yes	selectable replication factor	yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.	yes
MapReduce Offers an API for user-defined Map/Reduce methods		yes	Spark connector (open source): github.com/­Azure/­azure-kusto-spark	no
Consistency concepts Methods to ensure consistency in a distributed system	Immediate Consistency or Eventual Consistency depending on configuration	Eventual Consistency Immediate Consistency	Eventual Consistency Immediate Consistency	Immediate Consistency
Foreign keys Referential integrity	no	no	no	no
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	Atomic execution of specific operations	no	no	ACID
Concurrency Support for concurrent manipulation of data	yes	yes	yes	yes
Durability Support for making data persistent	yes	yes	yes	yes
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.	yes		no
User concepts Access control	LDAP bind authentication	no Can implement custom security layer via applications	Azure Active Directory Authentication	Access rights can be defined down to the item level
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More resources
	Atos Standard Common Repository	FatDB	Microsoft Azure Data Explorer	OpenQM also called QM
Recent citations in the news	Infographic: What makes a Mobile Operator's setup future proof? 10 February 2024, Atos provided by Google News		We’re retiring Azure Time Series Insights on 7 July 2024 – transition to Azure Data Explorer | Azure updates 31 May 2024, azure.microsoft.com Update records in a Kusto Database (public preview) | Azure updates 20 February 2024, azure.microsoft.com Public Preview: Azure Data Explorer connector for Apache Flink | Azure updates 8 January 2024, azure.microsoft.com Announcing General Availability to migrate Virtual Network injected Azure Data Explorer Cluster to Private Endpoints ... 5 February 2024, azure.microsoft.com New Features for graph-match KQL Operator: Enhanced Pattern Matching and Cycle Control | Azure updates 24 January 2024, azure.microsoft.com provided by Google News

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