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DBMS > Atos Standard Common Repository vs. GridDB vs. Hazelcast vs. Microsoft Azure AI Search

System Properties Comparison Atos Standard Common Repository vs. GridDB vs. Hazelcast vs. Microsoft Azure AI Search

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonGridDB  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure AI Search  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 DataA widely adopted in-memory data gridSearch-as-a-service for web and mobile app development
Primary database modelDocument store
Key-value store
Time Series DBMSKey-value storeSearch engine
Secondary database modelsKey-value store
Relational DBMS
Document store infoJSON support with IMDG 3.12Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score5.52
Rank#59  Overall
#6  Search engines
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorygriddb.nethazelcast.comazure.microsoft.com/­en-us/­services/­search
Technical documentationdocs.griddb.nethazelcast.org/­imdg/­docslearn.microsoft.com/­en-us/­azure/­search
DeveloperAtos Convergence CreatorsToshiba CorporationHazelcastMicrosoft
Initial release2016201320082015
Current release17035.1, August 20225.3.6, November 2023V1
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2; commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++Java
Server operating systemsLinuxLinuxAll OS with a Java VMhosted
Data schemeSchema and schema-less with LDAP viewsyesschema-freeyes
Typing infopredefined data types such as float or dateoptionalyes infonumerical, string, blob, geometry, boolean, timestampyesyes
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 infothe object must implement a serialization strategyno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query languageno
APIs and other access methodsLDAPJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
RESTful HTTP API
Supported programming languagesAll languages with LDAP bindingsC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C#
Java
JavaScript
Python
Server-side scripts infoStored proceduresnonoyes infoEvent Listeners, Executor Servicesno
Triggersyesyesyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyes infoReplicated Mapyes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACID at container levelone or two-phase-commit; repeatable reads; read commitedno
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 authenticationAccess rights for users can be defined per databaseRole-based access controlyes infousing Azure authentication
More information provided by the system vendor
Atos Standard Common RepositoryGridDBHazelcastMicrosoft Azure AI Search
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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Atos Standard Common RepositoryGridDBHazelcastMicrosoft Azure AI Search
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