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DBMS > Atos Standard Common Repository vs. Brytlyt vs. Rockset vs. Spark SQL

System Properties Comparison Atos Standard Common Repository vs. Brytlyt vs. Rockset vs. Spark SQL

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonBrytlyt  Xexclude from comparisonRockset  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 GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLA scalable, reliable search and analytics service in the cloud, built on RocksDBSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Relational DBMSDocument storeRelational DBMS
Secondary database modelsRelational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#276  Overall
#127  Relational DBMS
Score0.82
Rank#212  Overall
#36  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorybrytlyt.iorockset.comspark.apache.org/­sql
Technical documentationdocs.brytlyt.iodocs.rockset.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAtos Convergence CreatorsBrytlytRocksetApache Software Foundation
Initial release2016201620192014
Current release17035.0, August 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen 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 languageJavaC, C++ and CUDAC++Scala
Server operating systemsLinuxLinux
OS X
Windows
hostedLinux
OS X
Windows
Data schemeSchema and schema-less with LDAP viewsyesschema-freeyes
Typing infopredefined data types such as float or dateoptionalyesdynamic typingyes
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.yesyes infospecific XML-type available, but no XML query functionality.no infoingestion from XML files supportedno
Secondary indexesyesyesall fields are automatically indexedno
SQL infoSupport of SQLnoyesRead-only SQL queries, including JOINsSQL-like DML and DDL statements
APIs and other access methodsLDAPADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP RESTJDBC
ODBC
Supported programming languagesAll languages with LDAP bindings.Net
C
C++
Delphi
Java
Perl
Python
Tcl
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functions infoin PL/pgSQLnono
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionAutomatic shardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyesnone
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 ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDnono
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.yesno
User concepts infoAccess controlLDAP bind authenticationfine grained access rights according to SQL-standardAccess rights for users and organizations can be defined via Rockset consoleno

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Atos Standard Common RepositoryBrytlytRocksetSpark SQL
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