DBMS > Atos Standard Common Repository vs. Hawkular Metrics vs. Postgres-XL vs. Riak KV

System Properties Comparison Atos Standard Common Repository vs. Hawkular Metrics vs. Postgres-XL vs. Riak KV

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Editorial information provided by DB-Engines
Name	Atos Standard Common Repository  Xexclude from comparison	Hawkular Metrics  Xexclude from comparison	Postgres-XL  Xexclude from comparison	Riak KV  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.	Based on PostgreSQL enhanced with MPP and write-scale-out cluster features	Distributed, fault tolerant key-value store
Primary database model	Document store Key-value store	Time Series DBMS	Relational DBMS	Key-value store with links between data sets and object tags for the creation of secondary indexes
Secondary database models			Document store Spatial DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart		Score 0.08 Rank #366   Overall #39   Time Series DBMS	Score 0.53 Rank #254   Overall #117   Relational DBMS	Score 4.01 Rank #79   Overall #9   Key-value stores
Website	atos.net/en/convergence-creators/portfolio/standard-common-repository	www.hawkular.org	www.postgres-xl.org
Technical documentation		www.hawkular.org/­hawkular-metrics/­docs/­user-guide	www.postgres-xl.org/­documentation	www.tiot.jp/­riak-docs/­riak/­kv/­latest
Developer	Atos Convergence Creators	Community supported by Red Hat		OpenSource, formerly Basho Technologies
Initial release	2016	2014	2014 since 2012, originally named StormDB	2009
Current release	1703		10 R1, October 2018	3.2.0, December 2022
License Commercial or Open Source	commercial	Open Source Apache 2.0	Open Source Mozilla public license	Open Source Apache version 2, commercial enterprise edition
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	Erlang
Server operating systems	Linux	Linux OS X Windows	Linux macOS	Linux OS X
Data scheme	Schema and schema-less with LDAP views	schema-free	yes	schema-free
Typing predefined data types such as float or date	optional	yes	yes	no
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	yes XML type, but no XML query functionality	no
Secondary indexes	yes	no	yes	restricted
SQL Support of SQL	no	no	yes distributed, parallel query execution	no
APIs and other access methods	LDAP	HTTP REST	ADO.NET JDBC native C library ODBC streaming API for large objects	HTTP API Native Erlang Interface
Supported programming languages	All languages with LDAP bindings	Go Java Python Ruby	.Net C C++ Delphi Erlang Java JavaScript (Node.js) Perl PHP Python Tcl	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
Server-side scripts Stored procedures	no	no	user defined functions	Erlang
Triggers	yes	yes via Hawkular Alerting	yes	yes pre-commit hooks and post-commit hooks
Partitioning methods Methods for storing different data on different nodes	Sharding cell division	Sharding based on Cassandra	horizontal partitioning	Sharding no "single point of failure"
Replication methods Methods for redundantly storing data on multiple nodes	yes	selectable replication factor based on Cassandra		selectable replication factor
MapReduce Offers an API for user-defined Map/Reduce methods		no	no	yes
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	Immediate Consistency	Eventual Consistency
Foreign keys Referential integrity	no	no	yes	no links between data sets can be stored
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	Atomic execution of specific operations	no	ACID MVCC	no
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
User concepts Access control	LDAP bind authentication	no	fine grained access rights according to SQL-standard	yes, using Riak Security
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More resources
	Atos Standard Common Repository	Hawkular Metrics	Postgres-XL	Riak KV
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		Basho Revamps Riak Open-Source Database 22 September 2023, InformationWeek A Critique of Resizable Hash Tables: Riak Core & Random Slicing 26 August 2018, InfoQ.com Basho to Bolster Riak with DB Plug-Ins 5 May 2014, Datanami Riak NoSQL snapped up by Bet365 12 September 2017, ComputerWeekly.com Basho launches complete NoSQL software kit - DCD 28 May 2015, DatacenterDynamics provided by Google News

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