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DBMS > Atos Standard Common Repository vs. Google BigQuery vs. GridDB

System Properties Comparison Atos Standard Common Repository vs. Google BigQuery vs. GridDB

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonGridDB  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 networksLarge scale data warehouse service with append-only tablesScalable in-memory time series database optimized for IoT and Big Data
Primary database modelDocument store
Key-value store
Relational DBMSTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score61.90
Rank#19  Overall
#13  Relational DBMS
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorycloud.google.com/­bigquerygriddb.net
Technical documentationcloud.google.com/­bigquery/­docsdocs.griddb.net
DeveloperAtos Convergence CreatorsGoogleToshiba Corporation
Initial release201620102013
Current release17035.1, August 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemsLinuxhostedLinux
Data schemeSchema and schema-less with LDAP viewsyesyes
Typing infopredefined data types such as float or dateoptionalyesyes infonumerical, string, blob, geometry, boolean, timestamp
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.yesnono
Secondary indexesyesnoyes
SQL infoSupport of SQLnoyesSQL92, SQL-like TQL (Toshiba Query Language)
APIs and other access methodsLDAPRESTful HTTP/JSON APIJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesAll languages with LDAP bindings.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functions infoin JavaScriptno
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsno infoSince BigQuery is designed for querying dataACID at container level
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlLDAP bind authenticationAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Access rights for users can be defined per database
More information provided by the system vendor
Atos Standard Common RepositoryGoogle BigQueryGridDB
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 RepositoryGoogle BigQueryGridDB
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