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

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

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonBigchainDB  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 networksBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsCloud-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
Document storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.87
Rank#190  Overall
#30  Document stores
Score46.54
Rank#23  Overall
#15  Relational DBMS
Score20.56
Rank#34  Overall
#20  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.bigchaindb.comwww.snowflake.comspark.apache.org/­sql
Technical documentationbigchaindb.readthedocs.io/­en/­latestdocs.snowflake.net/­manuals/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAtos Convergence CreatorsSnowflake Computing Inc.Apache Software Foundation
Initial release2016201620142014
Current release17033.1.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoAGPL v3commercialOpen 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 languageJavaPythonScala
Server operating systemsLinuxLinuxhostedLinux
OS X
Windows
Data schemeSchema and schema-less with LDAP viewsschema-freeyes infosupport of semi-structured data formats (JSON, XML, Avro)yes
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.yesnoyesno
Secondary indexesyesno
SQL infoSupport of SQLnonoyesSQL-like DML and DDL statements
APIs and other access methodsLDAPCLI Client
RESTful HTTP API
CLI Client
JDBC
ODBC
JDBC
ODBC
Supported programming languagesAll languages with LDAP bindingsGo
Haskell
Java
JavaScript
Python
Ruby
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functionsno
Triggersyesno infosimilar concept for controling cloud resourcesno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingyesyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factoryesnone
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 configurationImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes,with MongoDB ord RethinkDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlLDAP bind authenticationyesUsers with fine-grained authorization concept, user roles and pluggable authenticationno

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More resources
Atos Standard Common RepositoryBigchainDBSnowflakeSpark SQL
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