DBMS > Atos Standard Common Repository vs. EventStoreDB vs. Heroic vs. Infobright

System Properties Comparison Atos Standard Common Repository vs. EventStoreDB vs. Heroic vs. Infobright

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Editorial information provided by DB-Engines
Name	Atos Standard Common Repository  Xexclude from comparison	EventStoreDB  Xexclude from comparison	Heroic  Xexclude from comparison	Infobright  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	Industrial-strength, open-source database solution built from the ground up for event sourcing.	Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch	High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend
Primary database model	Document store Key-value store	Event Store	Time Series DBMS	Relational DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart		Score 1.19 Rank #173   Overall #1   Event Stores	Score 0.46 Rank #265   Overall #22   Time Series DBMS	Score 1.02 Rank #192   Overall #90   Relational DBMS
Website	atos.net/en/convergence-creators/portfolio/standard-common-repository	www.eventstore.com	github.com/­spotify/­heroic	ignitetech.com/­softwarelibrary/­infobrightdb
Technical documentation		developers.eventstore.com	spotify.github.io/­heroic
Developer	Atos Convergence Creators	Event Store Limited	Spotify	Ignite Technologies Inc.; formerly InfoBright Inc.
Initial release	2016	2012	2014	2005
Current release	1703	21.2, February 2021
License Commercial or Open Source	commercial	Open Source	Open Source Apache 2.0	commercial The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016
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		Java	C
Server operating systems	Linux	Linux Windows		Linux Windows
Data scheme	Schema and schema-less with LDAP views		schema-free	yes
Typing predefined data types such as float or date	optional		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
Secondary indexes	yes		yes via Elasticsearch	no Knowledge Grid Technology used instead
SQL Support of SQL	no		no	yes
APIs and other access methods	LDAP		HQL (Heroic Query Language, a JSON-based language) HTTP API	ADO.NET JDBC ODBC
Supported programming languages	All languages with LDAP bindings			.Net C C# C++ D Eiffel Erlang Haskell Java Objective-C OCaml Perl PHP Python Ruby Scheme Tcl
Server-side scripts Stored procedures	no		no	no
Triggers	yes		no	no
Partitioning methods Methods for storing different data on different nodes	Sharding cell division		Sharding	none
Replication methods Methods for redundantly storing data on multiple nodes	yes		yes	Source-replica replication
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	Immediate Consistency
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	ACID
Concurrency Support for concurrent manipulation of data	yes		yes	yes
Durability Support for making data persistent	yes		yes	yes
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.	yes		no	yes
User concepts Access control	LDAP bind authentication			fine grained access rights according to SQL-standard exploiting MySQL or PostgreSQL frontend capabilities
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More resources
	Atos Standard Common Repository	EventStoreDB	Heroic	Infobright
Recent citations in the news			Review: Google Bigtable scales with ease 7 September 2016, InfoWorld provided by Google News

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