DBMS > Atos Standard Common Repository vs. Hawkular Metrics vs. Riak TS vs. TimesTen

System Properties Comparison Atos Standard Common Repository vs. Hawkular Metrics vs. Riak TS vs. TimesTen

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Editorial information provided by DB-Engines
Name	Atos Standard Common Repository  Xexclude from comparison	Hawkular Metrics  Xexclude from comparison	Riak TS  Xexclude from comparison	TimesTen  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	Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.	Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV	In-Memory RDBMS compatible to Oracle
Primary database model	Document store Key-value store	Time Series DBMS	Time Series DBMS	Relational DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart		Score 0.08 Rank #366   Overall #39   Time Series DBMS	Score 0.28 Rank #307   Overall #27   Time Series DBMS	Score 1.36 Rank #161   Overall #75   Relational DBMS
Website	atos.net/en/convergence-creators/portfolio/standard-common-repository	www.hawkular.org		www.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentation		www.hawkular.org/­hawkular-metrics/­docs/­user-guide	www.tiot.jp/­riak-docs/­riak/­ts/­latest	docs.oracle.com/­database/­timesten-18.1
Developer	Atos Convergence Creators	Community supported by Red Hat	Open Source, formerly Basho Technologies	Oracle, TimesTen Performance Software, HP originally founded in HP Labs it was acquired by Oracle in 2005
Initial release	2016	2014	2015	1998
Current release	1703		3.0.0, September 2022	11 Release 2 (11.2.2.8.0)
License Commercial or Open Source	commercial	Open Source Apache 2.0	Open Source	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	Java	Erlang
Server operating systems	Linux	Linux OS X Windows	Linux OS X	AIX HP-UX Linux OS X Solaris SPARC/x86 Windows
Data scheme	Schema and schema-less with LDAP views	schema-free	schema-free	yes
Typing predefined data types such as float or date	optional	yes	no	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	no
Secondary indexes	yes	no	restricted	yes
SQL Support of SQL	no	no	yes, limited	yes
APIs and other access methods	LDAP	HTTP REST	HTTP API Native Erlang Interface	JDBC ODBC ODP.NET Oracle Call Interface (OCI)
Supported programming languages	All languages with LDAP bindings	Go Java Python Ruby	C unofficial client library C# C++ unofficial client library Clojure unofficial client library Dart unofficial client library Erlang Go unofficial client library Groovy unofficial client library Haskell unofficial client library Java JavaScript unofficial client library Lisp unofficial client library Perl unofficial client library PHP Python Ruby Scala unofficial client library Smalltalk unofficial client library	C C++ Java PL/SQL
Server-side scripts Stored procedures	no	no	Erlang	PL/SQL
Triggers	yes	yes via Hawkular Alerting	yes pre-commit hooks and post-commit hooks	no
Partitioning methods Methods for storing different data on different nodes	Sharding cell division	Sharding based on Cassandra	Sharding	none
Replication methods Methods for redundantly storing data on multiple nodes	yes	selectable replication factor based on Cassandra	selectable replication factor	Multi-source replication Source-replica replication
MapReduce Offers an API for user-defined Map/Reduce methods		no	yes	no
Consistency concepts Methods to ensure consistency in a distributed system	Immediate Consistency or Eventual Consistency depending on configuration	Eventual Consistency based on Cassandra Immediate Consistency based on Cassandra	Eventual Consistency	Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys Referential integrity	no	no	no links between datasets can be stored	yes
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 by means of logfiles and checkpoints
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	no	no	fine grained access rights according to SQL-standard
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More resources
	Atos Standard Common Repository	Hawkular Metrics	Riak TS	TimesTen
Recent citations in the news		Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived… • DEVCLASS 5 June 2019, DevClass provided by Google News	New Basho Data Platform Provides Operational Simplicity for Enterprise Big Data Applications 7 June 2015, insideBIGDATA Best open source databases for IoT applications 26 May 2017, Open Source For You provided by Google News

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