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DBMS > Atos Standard Common Repository vs. Firebolt vs. GridDB vs. Postgres-XL vs. Prometheus

System Properties Comparison Atos Standard Common Repository vs. Firebolt vs. GridDB vs. Postgres-XL vs. Prometheus

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonFirebolt  Xexclude from comparisonGridDB  Xexclude from comparisonPostgres-XL  Xexclude from comparisonPrometheus  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 networksHighly scalable cloud data warehouse and analytics product infoForked from ClickhouseScalable in-memory time series database optimized for IoT and Big DataBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresOpen-source Time Series DBMS and monitoring system
Primary database modelDocument store
Key-value store
Relational DBMSTime Series DBMSRelational DBMSTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.73
Rank#140  Overall
#63  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.firebolt.iogriddb.netwww.postgres-xl.orgprometheus.io
Technical documentationdocs.firebolt.iodocs.griddb.netwww.postgres-xl.org/­documentationprometheus.io/­docs
DeveloperAtos Convergence CreatorsFirebolt Analytics Inc.Toshiba Corporation
Initial release2016202020132014 infosince 2012, originally named StormDB2015
Current release17035.1, August 202210 R1, October 2018
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoMozilla public licenseOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++CGo
Server operating systemsLinuxhostedLinuxLinux
macOS
Linux
Windows
Data schemeSchema and schema-less with LDAP viewsyesyesyesyes
Typing infopredefined data types such as float or dateoptionalyesyes infonumerical, string, blob, geometry, boolean, timestampyesNumeric data only
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.yesnoyes infoXML type, but no XML query functionalityno infoImport of XML data possible
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLnoyesSQL92, SQL-like TQL (Toshiba Query Language)yes infodistributed, parallel query executionno
APIs and other access methodsLDAP.Net
ODBC
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP/JSON API
Supported programming languagesAll languages with LDAP bindingsGo
JavaScript (Node.js)
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresnononouser defined functionsno
Triggersyesnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardinghorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesdepending on storage layerSource-replica replicationyes infoby Federation
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate consistency within container, eventual consistency across containersImmediate Consistencynone
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACID at container levelACID infoMVCCno
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 authenticationAccess rights for users can be defined per databasefine grained access rights according to SQL-standardno
More information provided by the system vendor
Atos Standard Common RepositoryFireboltGridDBPostgres-XLPrometheus
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Atos Standard Common RepositoryFireboltGridDBPostgres-XLPrometheus
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