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DBMS > Atos Standard Common Repository vs. GigaSpaces vs. Google Cloud Datastore vs. Hive

System Properties Comparison Atos Standard Common Repository vs. GigaSpaces vs. Google Cloud Datastore vs. Hive

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonGigaSpaces  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHive  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 TransactionsAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platformdata warehouse software for querying and managing large distributed datasets, built on Hadoop
Primary database modelDocument store
Key-value store
Document store
Object oriented DBMS infoValues are user defined objects
Document storeRelational DBMS
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.gigaspaces.comcloud.google.com/­datastorehive.apache.org
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmlcloud.google.com/­datastore/­docscwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperAtos Convergence CreatorsGigaspaces TechnologiesGoogleApache Software Foundation infoinitially developed by Facebook
Initial release2016200020082012
Current release170315.5, September 20203.1.3, April 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; Commercial licenses availablecommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, C++, .NetJava
Server operating systemsLinuxLinux
macOS
Solaris
Windows
hostedAll OS with a Java VM
Data schemeSchema and schema-less with LDAP viewsschema-freeschema-freeyes
Typing infopredefined data types such as float or dateoptionalyesyes, details hereyes
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 metadatano
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoSQL-99 for query and DML statementsSQL-like query language (GQL)SQL-like DML and DDL statements
APIs and other access methodsLDAPGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Supported programming languagesAll languages with LDAP bindings.Net
C++
Java
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
PHP
Python
Server-side scripts infoStored proceduresnoyesusing Google App Engineyes infouser defined functions and integration of map-reduce
Triggersyesyes, event driven architectureCallbacks using the Google Apps Engineno
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
Multi-source replication using Paxosselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsyes infousing Google Cloud Dataflowyes infoquery execution via MapReduce
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 or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual Consistency
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
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.yesyesno
User concepts infoAccess controlLDAP bind authenticationRole-based access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles

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More resources
Atos Standard Common RepositoryGigaSpacesGoogle Cloud DatastoreHive
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