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DBMS > Atos Standard Common Repository vs. GigaSpaces vs. GridDB vs. Prometheus

System Properties Comparison Atos Standard Common Repository vs. GigaSpaces vs. GridDB vs. Prometheus

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonGigaSpaces  Xexclude from comparisonGridDB  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 networksHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsScalable in-memory time series database optimized for IoT and Big DataOpen-source Time Series DBMS and monitoring system
Primary database modelDocument store
Key-value store
Document store
Object oriented DBMS infoValues are user defined objects
Time Series DBMSTime Series DBMS
Secondary database modelsGraph DBMS
Search engine
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.02
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Score7.92
Rank#51  Overall
#2  Time Series DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.gigaspaces.comgriddb.netprometheus.io
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmldocs.griddb.netprometheus.io/­docs
DeveloperAtos Convergence CreatorsGigaspaces TechnologiesToshiba Corporation
Initial release2016200020132015
Current release170315.5, September 20205.1, August 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, C++, .NetC++Go
Server operating systemsLinuxLinux
macOS
Solaris
Windows
LinuxLinux
Windows
Data schemeSchema and schema-less with LDAP viewsschema-freeyesyes
Typing infopredefined data types such as float or dateoptionalyesyes infonumerical, string, blob, geometry, boolean, timestampNumeric 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.yesno infoXML can be used for describing objects metadatanono infoImport of XML data possible
Secondary indexesyesyesyesno
SQL infoSupport of SQLnoSQL-99 for query and DML statementsSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsLDAPGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
RESTful HTTP/JSON API
Supported programming languagesAll languages with LDAP bindings.Net
C++
Java
Python
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresnoyesnono
Triggersyesyes, event driven architectureyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Source-replica replicationyes infoby Federation
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate consistency within container, eventual consistency across containersnone
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDACID at container levelno
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.yesyesyesno
User concepts infoAccess controlLDAP bind authenticationRole-based access controlAccess rights for users can be defined per databaseno
More information provided by the system vendor
Atos Standard Common RepositoryGigaSpacesGridDBPrometheus
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 RepositoryGigaSpacesGridDBPrometheus
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