DBMS > Atos Standard Common Repository vs. chDB vs. IBM Db2 Event Store vs. IRONdb

System Properties Comparison Atos Standard Common Repository vs. chDB vs. IBM Db2 Event Store vs. IRONdb

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Editorial information provided by DB-Engines
Name	Atos Standard Common Repository  Xexclude from comparison	chDB  Xexclude from comparison	IBM Db2 Event Store  Xexclude from comparison	IRONdb  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	An embedded SQL OLAP Engine powered by ClickHouse	Distributed Event Store optimized for Internet of Things use cases	A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity
Primary database model	Document store Key-value store	Relational DBMS	Event Store Time Series DBMS	Time Series DBMS
Secondary database models		Time Series DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart		Score 0.07 Rank #376   Overall #158   Relational DBMS	Score 0.27 Rank #309   Overall #2   Event Stores #28   Time Series DBMS
Website	atos.net/en/convergence-creators/portfolio/standard-common-repository	github.com/­chdb-io/­chdb	www.ibm.com/­products/­db2-event-store	www.circonus.com/solutions/time-series-database/
Technical documentation		doc.chdb.io	www.ibm.com/­docs/­en/­db2-event-store	docs.circonus.com/irondb/category/getting-started
Developer	Atos Convergence Creators		IBM	Circonus LLC.
Initial release	2016	2023	2017	2017
Current release	1703		2.0	V0.10.20, January 2018
License Commercial or Open Source	commercial	Open Source Apache Version 2.0	commercial free developer edition available	commercial
Cloud-based only Only available as a cloud service	no	no	no	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 and C++
Server operating systems	Linux	server-less	Linux Linux, macOS, Windows for the developer addition	Linux
Data scheme	Schema and schema-less with LDAP views		yes	schema-free
Typing predefined data types such as float or date	optional		yes	yes text, numeric, histograms
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
Secondary indexes	yes		no	no
SQL Support of SQL	no	Close to ANSI SQL (SQL/JSON + extensions)	yes through the embedded Spark runtime	SQL-like query language (Circonus Analytics Query Language: CAQL)
APIs and other access methods	LDAP		ADO.NET DB2 Connect JDBC ODBC RESTful HTTP API	HTTP API
Supported programming languages	All languages with LDAP bindings	Bun C C++ Go JavaScript (Node.js) Python Rust	C C# C++ Cobol Delphi Fortran Go Java JavaScript (Node.js) Perl PHP Python R Ruby Scala Visual Basic	.Net C C++ Clojure Erlang Go Haskell Java JavaScript JavaScript (Node.js) Lisp Lua Perl PHP Python R Ruby Rust Scala
Server-side scripts Stored procedures	no		yes	yes, in Lua
Triggers	yes		no	no
Partitioning methods Methods for storing different data on different nodes	Sharding cell division		Sharding	Automatic, metric affinity per node
Replication methods Methods for redundantly storing data on multiple nodes	yes		Active-active shard replication	configurable replication factor, datacenter aware
MapReduce Offers an API for user-defined Map/Reduce methods			no	no
Consistency concepts Methods to ensure consistency in a distributed system	Immediate Consistency or Eventual Consistency depending on configuration		Eventual Consistency	Immediate consistency per node, eventual consistency across nodes
Foreign keys Referential integrity	no		no	no
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	Atomic execution of specific operations		no	no
Concurrency Support for concurrent manipulation of data	yes		No - written data is immutable	yes
Durability Support for making data persistent	yes		Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage	yes
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.	yes		yes	no
User concepts Access control	LDAP bind authentication		fine grained access rights according to SQL-standard	no
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More resources
	Atos Standard Common Repository	chDB	IBM Db2 Event Store	IRONdb
Recent citations in the news			Advancements in streaming data storage, real-time analysis and machine learning 25 July 2019, ibm.com How IBM Is Turning Db2 into an ‘AI Database’ 3 June 2019, Datanami Best cloud databases of 2022 4 October 2022, ITPro Why a robust data management strategy is essential today | IBM HDM 19 September 2019, Express Computer provided by Google 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

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