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

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

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonGridDB  Xexclude from comparisonPostgres-XL  Xexclude from comparisonPrometheus  Xexclude from comparisonReductStore  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 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 systemDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.
Primary database modelDocument store
Key-value store
Time Series DBMSRelational DBMSTime Series 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
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
Score0.05
Rank#384  Overall
#44  Time Series DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorygriddb.netwww.postgres-xl.orgprometheus.iogithub.com/­reductstore
www.reduct.store
Technical documentationdocs.griddb.netwww.postgres-xl.org/­documentationprometheus.io/­docswww.reduct.store/­docs
DeveloperAtos Convergence CreatorsToshiba CorporationReductStore LLC
Initial release201620132014 infosince 2012, originally named StormDB20152023
Current release17035.1, August 202210 R1, October 20181.9, March 2024
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoMozilla public licenseOpen Source infoApache 2.0Open Source infoBusiness Source License 1.1
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++CGoC++, Rust
Server operating systemsLinuxLinuxLinux
macOS
Linux
Windows
Docker
Linux
macOS
Windows
Data schemeSchema and schema-less with LDAP viewsyesyesyes
Typing infopredefined data types such as float or dateoptionalyes 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 indexesyesyesyesno
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)yes infodistributed, parallel query executionno
APIs and other access methodsLDAPJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP/JSON APIHTTP API
Supported programming languagesAll languages with LDAP bindingsC
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
C++
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresnonouser defined functionsno
Triggersyesyesyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardinghorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-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 RepositoryGridDBPostgres-XLPrometheusReductStore
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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More resources
Atos Standard Common RepositoryGridDBPostgres-XLPrometheusReductStore
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