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DBMS > Atos Standard Common Repository vs. Google Cloud Datastore vs. Heroic vs. InterSystems Caché vs. Microsoft Azure SQL Database

System Properties Comparison Atos Standard Common Repository vs. Google Cloud Datastore vs. Heroic vs. InterSystems Caché vs. Microsoft Azure SQL Database

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHeroic  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchA multi-model DBMS and application serverDatabase as a Service offering with high compatibility to Microsoft SQL Server
Primary database modelDocument store
Key-value store
Document storeTime Series DBMSKey-value store
Object oriented DBMS
Relational DBMS
Relational DBMS
Secondary database modelsDocument storeDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorycloud.google.com/­datastoregithub.com/­spotify/­heroicwww.intersystems.com/­products/­cacheazure.microsoft.com/­en-us/­products/­azure-sql/­database
Technical documentationcloud.google.com/­datastore/­docsspotify.github.io/­heroicdocs.intersystems.comdocs.microsoft.com/­en-us/­azure/­azure-sql
DeveloperAtos Convergence CreatorsGoogleSpotifyInterSystemsMicrosoft
Initial release20162008201419972010
Current release17032018.1.4, May 2020V12
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC++
Server operating systemsLinuxhostedAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
hosted
Data schemeSchema and schema-less with LDAP viewsschema-freeschema-freedepending on used data modelyes
Typing infopredefined data types such as float or dateoptionalyes, details hereyesyesyes
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.yesnonoyesyes
Secondary indexesyesyesyes infovia Elasticsearchyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)noyesyes
APIs and other access methodsLDAPgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
.NET Client API
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
Supported programming languagesAll languages with LDAP bindings.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnousing Google App EnginenoyesTransact SQL
TriggersyesCallbacks using the Google Apps Enginenoyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using PaxosyesSource-replica replicationyes, with always 3 replicas available
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate 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
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlLDAP bind authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and rolesfine grained access rights according to SQL-standard

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More resources
Atos Standard Common RepositoryGoogle Cloud DatastoreHeroicInterSystems CachéMicrosoft Azure SQL Database infoformerly SQL Azure
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