DBMS > Atos Standard Common Repository vs. IRONdb vs. Microsoft Azure AI Search vs. Postgres-XL

System Properties Comparison Atos Standard Common Repository vs. IRONdb vs. Microsoft Azure AI Search vs. Postgres-XL

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Editorial information provided by DB-Engines
Name	Atos Standard Common Repository  Xexclude from comparison	IRONdb  Xexclude from comparison	Microsoft Azure AI Search  Xexclude from comparison	Postgres-XL  Xexclude from comparison
	This system has been discontinued and will be removed from the DB-Engines ranking.	IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
Description	Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks	A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity	Search-as-a-service for web and mobile app development	Based on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database model	Document store Key-value store	Time Series DBMS	Search engine	Relational DBMS
Secondary database models			Vector DBMS	Document store Spatial DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart			Score 5.52 Rank #59   Overall #6   Search engines	Score 0.53 Rank #254   Overall #117   Relational DBMS
Website	atos.net/en/convergence-creators/portfolio/standard-common-repository	www.circonus.com/solutions/time-series-database/	azure.microsoft.com/­en-us/­services/­search	www.postgres-xl.org
Technical documentation		docs.circonus.com/irondb/category/getting-started	learn.microsoft.com/­en-us/­azure/­search	www.postgres-xl.org/­documentation
Developer	Atos Convergence Creators	Circonus LLC.	Microsoft
Initial release	2016	2017	2015	2014 since 2012, originally named StormDB
Current release	1703	V0.10.20, January 2018	V1	10 R1, October 2018
License Commercial or Open Source	commercial	commercial	commercial	Open Source Mozilla public license
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	C and C++		C
Server operating systems	Linux	Linux	hosted	Linux macOS
Data scheme	Schema and schema-less with LDAP views	schema-free	yes	yes
Typing predefined data types such as float or date	optional	yes text, numeric, histograms	yes	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	no	no	yes XML type, but no XML query functionality
Secondary indexes	yes	no	yes	yes
SQL Support of SQL	no	SQL-like query language (Circonus Analytics Query Language: CAQL)	no	yes distributed, parallel query execution
APIs and other access methods	LDAP	HTTP API	RESTful HTTP API	ADO.NET JDBC native C library ODBC streaming API for large objects
Supported programming languages	All languages with LDAP bindings	.Net C C++ Clojure Erlang Go Haskell Java JavaScript JavaScript (Node.js) Lisp Lua Perl PHP Python R Ruby Rust Scala	C# Java JavaScript Python	.Net C C++ Delphi Erlang Java JavaScript (Node.js) Perl PHP Python Tcl
Server-side scripts Stored procedures	no	yes, in Lua	no	user defined functions
Triggers	yes	no	no	yes
Partitioning methods Methods for storing different data on different nodes	Sharding cell division	Automatic, metric affinity per node	Sharding Implicit feature of the cloud service	horizontal partitioning
Replication methods Methods for redundantly storing data on multiple nodes	yes	configurable replication factor, datacenter aware	yes Implicit feature of the cloud service
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	Immediate consistency per node, eventual consistency across nodes	Immediate Consistency	Immediate Consistency
Foreign keys Referential integrity	no	no	no	yes
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	Atomic execution of specific operations	no	no	ACID MVCC
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	no	no
User concepts Access control	LDAP bind authentication	no	yes using Azure authentication	fine grained access rights according to SQL-standard
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More resources
	Atos Standard Common Repository	IRONdb	Microsoft Azure AI Search	Postgres-XL
Recent citations in the news		Application observability firm Apica buys telemetry data startup Circonus and adds more funding 21 February 2024, SiliconANGLE News Apica Acquires Telemetry Data Management Pioneer Circonus And Lands New Funding 22 February 2024, Datanami Apica gets $6 million in funding and buys Circonus - 21 February 2024, Enterprise Times provided by Google News	Announcing updates to Azure AI Search to help organizations build and scale generative AI applications 4 April 2024, Microsoft Microsoft and ServiceNow at Knowledge 2024: Introducing generative AI innovation 13 June 2024, Microsoft Azure OpenAI Service: Transforming legal practices with generative AI solutions 12 June 2024, Microsoft Public Preview of Azure OpenAI and AI Search in-app connectors for Logic Apps (Standard) | Azure updates 2 April 2024, Microsoft Raise the bar on AI-powered app development with Azure Database for PostgreSQL 5 June 2024, Microsoft provided by Google News

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