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DBMS > Atos Standard Common Repository vs. Spark SQL vs. TigerGraph vs. Valentina Server

System Properties Comparison Atos Standard Common Repository vs. Spark SQL vs. TigerGraph vs. Valentina Server

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonSpark SQL  Xexclude from comparisonTigerGraph  Xexclude from comparisonValentina Server  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 networksSpark SQL is a component on top of 'Spark Core' for structured data processingA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-timeObject-relational database and reports server
Primary database modelDocument store
Key-value store
Relational DBMSGraph DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.83
Rank#139  Overall
#13  Graph DBMS
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositoryspark.apache.org/­sqlwww.tigergraph.comwww.valentina-db.net
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.tigergraph.comvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperAtos Convergence CreatorsApache Software FoundationParadigma Software
Initial release2016201420171999
Current release17033.5.0 ( 2.13), September 20235.7.5
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScalaC++
Server operating systemsLinuxLinux
OS X
Windows
LinuxLinux
OS X
Windows
Data schemeSchema and schema-less with LDAP viewsyesyesyes
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.yesnono
Secondary indexesyesnoyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like query language (GSQL)yes
APIs and other access methodsLDAPJDBC
ODBC
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
ODBC
Supported programming languagesAll languages with LDAP bindingsJava
Python
R
Scala
C++
Java
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresnonoyesyes
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.yesnonoyes
User concepts infoAccess controlLDAP bind authenticationnoRole-based access controlfine grained access rights according to SQL-standard

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More resources
Atos Standard Common RepositorySpark SQLTigerGraphValentina Server
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