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DBMS > Atos Standard Common Repository vs. Badger vs. GeoSpock vs. Spark SQL

System Properties Comparison Atos Standard Common Repository vs. Badger vs. GeoSpock vs. Spark SQL

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonBadger  Xexclude from comparisonGeoSpock  Xexclude from comparisonSpark SQL  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Spatial and temporal data processing engine for extreme data scaleSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Key-value storeRelational DBMSRelational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorygithub.com/­dgraph-io/­badgergeospock.comspark.apache.org/­sql
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAtos Convergence CreatorsDGraph LabsGeoSpockApache Software Foundation
Initial release201620172014
Current release17032.0, September 20193.5.0 ( 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoJava, JavascriptScala
Server operating systemsLinuxBSD
Linux
OS X
Solaris
Windows
hostedLinux
OS X
Windows
Data schemeSchema and schema-less with LDAP viewsschema-freeyesyes
Typing infopredefined data types such as float or dateoptionalnoyesyes
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 indexesyesnotemporal, categoricalno
SQL infoSupport of SQLnonoANSI SQL for query only (using Presto)SQL-like DML and DDL statements
APIs and other access methodsLDAPJDBCJDBC
ODBC
Supported programming languagesAll languages with LDAP bindingsGoJava
Python
R
Scala
Server-side scripts infoStored proceduresnononono
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionnoneAutomatic shardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesnonenone
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 configurationnoneImmediate Consistency
Foreign keys infoReferential integritynononono
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.yesnonono
User concepts infoAccess controlLDAP bind authenticationnoAccess rights for users can be defined per tableno

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More resources
Atos Standard Common RepositoryBadgerGeoSpockSpark SQL
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