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DBMS > Atos Standard Common Repository vs. Blueflood vs. Snowflake vs. Spark SQL

System Properties Comparison Atos Standard Common Repository vs. Blueflood vs. Snowflake vs. Spark SQL

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonBlueflood  Xexclude from comparisonSnowflake  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 networksScalable TimeSeries DBMS based on CassandraCloud-based data warehousing service for structured and semi-structured dataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Time Series DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.06
Rank#353  Overall
#34  Time Series DBMS
Score121.33
Rank#9  Overall
#6  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositoryblueflood.iowww.snowflake.comspark.apache.org/­sql
Technical documentationgithub.com/­rax-maas/­blueflood/­wikidocs.snowflake.net/­manuals/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAtos Convergence CreatorsRackspaceSnowflake Computing Inc.Apache Software Foundation
Initial release2016201320142014
Current release17033.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaScala
Server operating systemsLinuxLinux
OS X
hostedLinux
OS X
Windows
Data schemeSchema and schema-less with LDAP viewspredefined schemeyes infosupport of semi-structured data formats (JSON, XML, Avro)yes
Typing infopredefined data types such as float or dateoptionalyesyesyes
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.yesnoyesno
Secondary indexesyesnono
SQL infoSupport of SQLnonoyesSQL-like DML and DDL statements
APIs and other access methodsLDAPHTTP RESTCLI Client
JDBC
ODBC
JDBC
ODBC
Supported programming languagesAll languages with LDAP bindingsJavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonouser defined functionsno
Triggersyesnono infosimilar concept for controling cloud resourcesno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionSharding infobased on Cassandrayesyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor infobased on Cassandrayesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnoACIDno
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.yesnonono
User concepts infoAccess controlLDAP bind authenticationnoUsers with fine-grained authorization concept, user roles and pluggable authenticationno

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More resources
Atos Standard Common RepositoryBluefloodSnowflakeSpark SQL
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