DBMS > Atos Standard Common Repository vs. IBM Db2 Event Store vs. IRONdb vs. Postgres-XL

System Properties Comparison Atos Standard Common Repository vs. IBM Db2 Event Store vs. IRONdb vs. Postgres-XL

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Editorial information provided by DB-Engines
Name	Atos Standard Common Repository  Xexclude from comparison	IBM Db2 Event Store  Xexclude from comparison	IRONdb  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	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	Based on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database model	Document store Key-value store	Event Store Time Series DBMS	Time Series DBMS	Relational DBMS
Secondary database models				Document store Spatial DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart		Score 0.27 Rank #309   Overall #2   Event Stores #28   Time Series DBMS		Score 0.53 Rank #254   Overall #117   Relational DBMS
Website	atos.net/en/convergence-creators/portfolio/standard-common-repository	www.ibm.com/­products/­db2-event-store	www.circonus.com/solutions/time-series-database/	www.postgres-xl.org
Technical documentation		www.ibm.com/­docs/­en/­db2-event-store	docs.circonus.com/irondb/category/getting-started	www.postgres-xl.org/­documentation
Developer	Atos Convergence Creators	IBM	Circonus LLC.
Initial release	2016	2017	2017	2014 since 2012, originally named StormDB
Current release	1703	2.0	V0.10.20, January 2018	10 R1, October 2018
License Commercial or Open Source	commercial	commercial free developer edition available	commercial	Open Source Mozilla public license
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++	C
Server operating systems	Linux	Linux Linux, macOS, Windows for the developer addition	Linux	Linux macOS
Data scheme	Schema and schema-less with LDAP views	yes	schema-free	yes
Typing predefined data types such as float or date	optional	yes	yes text, numeric, histograms	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	no	yes
SQL Support of SQL	no	yes through the embedded Spark runtime	SQL-like query language (Circonus Analytics Query Language: CAQL)	yes distributed, parallel query execution
APIs and other access methods	LDAP	ADO.NET DB2 Connect JDBC ODBC RESTful HTTP API	HTTP API	ADO.NET JDBC native C library ODBC streaming API for large objects
Supported programming languages	All languages with LDAP bindings	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	.Net C C++ Delphi Erlang Java JavaScript (Node.js) Perl PHP Python Tcl
Server-side scripts Stored procedures	no	yes	yes, in Lua	user defined functions
Triggers	yes	no	no	yes
Partitioning methods Methods for storing different data on different nodes	Sharding cell division	Sharding	Automatic, metric affinity per node	horizontal partitioning
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	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	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	No - written data is immutable	yes	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	yes
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.	yes	yes	no	no
User concepts Access control	LDAP bind authentication	fine grained access rights according to SQL-standard	no	fine grained access rights according to SQL-standard
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More resources
	Atos Standard Common Repository	IBM Db2 Event Store	IRONdb	Postgres-XL
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