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DBMS > Atos Standard Common Repository vs. Ehcache vs. Riak KV vs. Spark SQL

System Properties Comparison Atos Standard Common Repository vs. Ehcache vs. Riak KV vs. Spark SQL

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonEhcache  Xexclude from comparisonRiak KV  Xexclude from comparisonSpark SQL  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksA widely adopted Java cache with tiered storage optionsDistributed, fault tolerant key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Key-value storeKey-value store infowith links between data sets and object tags for the creation of secondary indexesRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.64
Rank#68  Overall
#8  Key-value stores
Score4.01
Rank#79  Overall
#9  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.ehcache.orgspark.apache.org/­sql
Technical documentationwww.ehcache.org/­documentationwww.tiot.jp/­riak-docs/­riak/­kv/­latestspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAtos Convergence CreatorsTerracotta Inc, owned by Software AGOpenSource, formerly Basho TechnologiesApache Software Foundation
Initial release2016200920092014
Current release17033.10.0, March 20223.2.0, December 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache version 2, commercial enterprise editionOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaErlangScala
Server operating systemsLinuxAll OS with a Java VMLinux
OS X
Linux
OS X
Windows
Data schemeSchema and schema-less with LDAP viewsschema-freeschema-freeyes
Typing infopredefined data types such as float or dateoptionalyesnoyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yesnonono
Secondary indexesyesnorestrictedno
SQL infoSupport of SQLnononoSQL-like DML and DDL statements
APIs and other access methodsLDAPJCacheHTTP API
Native Erlang Interface
JDBC
ODBC
Supported programming languagesAll languages with LDAP bindingsJavaC infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonoErlangno
Triggersyesyes infoCache Event Listenersyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionSharding infoby using Terracotta ServerSharding infono "single point of failure"yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoby using Terracotta Serverselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationTunable Consistency (Strong, Eventual, Weak)Eventual Consistency
Foreign keys infoReferential integritynonono infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsyes infosupports JTA and can work as an XA resourcenono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing a tiered cache-storage approachyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlLDAP bind authenticationnoyes, using Riak Securityno

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More resources
Atos Standard Common RepositoryEhcacheRiak KVSpark SQL
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