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DBMS > Atos Standard Common Repository vs. Hive vs. Riak TS vs. Spark SQL

System Properties Comparison Atos Standard Common Repository vs. Hive vs. Riak TS vs. Spark SQL

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonHive  Xexclude from comparisonRiak TS  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 networksdata warehouse software for querying and managing large distributed datasets, built on HadoopRiak TS is a distributed NoSQL database optimized for time series data and based on Riak KVSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Relational DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.20
Rank#319  Overall
#27  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositoryhive.apache.orgspark.apache.org/­sql
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homewww.tiot.jp/­riak-docs/­riak/­ts/­latestspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAtos Convergence CreatorsApache Software Foundation infoinitially developed by FacebookOpen Source, formerly Basho TechnologiesApache Software Foundation
Initial release2016201220152014
Current release17033.1.3, April 20223.0.0, September 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open SourceOpen 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 viewsyesschema-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.yesnono
Secondary indexesyesyesrestrictedno
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyes, limitedSQL-like DML and DDL statements
APIs and other access methodsLDAPJDBC
ODBC
Thrift
HTTP API
Native Erlang Interface
JDBC
ODBC
Supported programming languagesAll languages with LDAP bindingsC++
Java
PHP
Python
C 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 proceduresnoyes infouser defined functions and integration of map-reduceErlangno
Triggersyesnoyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factorselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono infolinks between datasets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlLDAP bind authenticationAccess rights for users, groups and rolesnono

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Atos Standard Common RepositoryHiveRiak TSSpark SQL
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