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DBMS > Atos Standard Common Repository vs. Galaxybase vs. Spark SQL vs. TigerGraph

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

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonGalaxybase  Xexclude from comparisonSpark SQL  Xexclude from comparisonTigerGraph  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, ACID-compliant native distributed parallel graph platformSpark 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-time
Primary database modelDocument store
Key-value store
Graph DBMSRelational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#383  Overall
#39  Graph DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorygalaxybase.comspark.apache.org/­sqlwww.tigergraph.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.tigergraph.com
DeveloperAtos Convergence CreatorsChuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司Apache Software Foundation
Initial release2016201720142017
Current release1703Nov 20, November 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial
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 languageJavaC and JavaScalaC++
Server operating systemsLinuxLinuxLinux
OS X
Windows
Linux
Data schemeSchema and schema-less with LDAP viewsStrong typed schemayesyes
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.yesnonono
Secondary indexesyesyesno
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsSQL-like query language (GSQL)
APIs and other access methodsLDAPBrowser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API
JDBC
ODBC
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesAll languages with LDAP bindingsGo
Java
Python
Java
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresnouser defined procedures and functionsnoyes
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesnone
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 configurationImmediate Consistency
Foreign keys infoReferential integritynoyes infoRelationships in graphsnoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDnoACID
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.yesyesnono
User concepts infoAccess controlLDAP bind authenticationRole-based access controlnoRole-based access control

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More resources
Atos Standard Common RepositoryGalaxybaseSpark SQLTigerGraph
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