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DBMS > Atos Standard Common Repository vs. Google Cloud Firestore vs. GridGain vs. Teradata Aster

System Properties Comparison Atos Standard Common Repository vs. Google Cloud Firestore vs. GridGain vs. Teradata Aster

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonGridGain  Xexclude from comparisonTeradata Aster  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.GridGain is an in-memory computing platform, built on Apache IgnitePlatform for big data analytics on multistructured data sources and types
Primary database modelDocument store
Key-value store
Document storeKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.36
Rank#53  Overall
#9  Document stores
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositoryfirebase.google.com/­products/­firestorewww.gridgain.com
Technical documentationfirebase.google.com/­docs/­firestorewww.gridgain.com/­docs/­index.html
DeveloperAtos Convergence CreatorsGoogleGridGain Systems, Inc.Teradata
Initial release2016201720072005
Current release1703GridGain 8.5.1
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, C++, .Net
Server operating systemsLinuxhostedLinux
OS X
Solaris
Windows
Linux
Data schemeSchema and schema-less with LDAP viewsschema-freeyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateoptionalyesyesyes
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.yesnoyesyes infoin Aster File Store
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnonoANSI-99 for query and DML statements, subset of DDLyes
APIs and other access methodsLDAPAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesAll languages with LDAP bindingsGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnoyes, Firebase Rules & Cloud Functionsyes (compute grid and cache interceptors can be used instead)R packages
Triggersyesyes, with Cloud Functionsyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationyes (replicated cache)yes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud Dataflowyes (compute grid and hadoop accelerator)yes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsyesACIDACID
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 authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Security Hooks for custom implementationsfine grained access rights according to SQL-standard

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More resources
Atos Standard Common RepositoryGoogle Cloud FirestoreGridGainTeradata Aster
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