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DBMS > Atos Standard Common Repository vs. Google Cloud Datastore vs. HBase vs. Prometheus

System Properties Comparison Atos Standard Common Repository vs. Google Cloud Datastore vs. HBase vs. Prometheus

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHBase  Xexclude from comparisonPrometheus  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 networksAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWide-column store based on Apache Hadoop and on concepts of BigTableOpen-source Time Series DBMS and monitoring system
Primary database modelDocument store
Key-value store
Document storeWide column storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorycloud.google.com/­datastorehbase.apache.orgprometheus.io
Technical documentationcloud.google.com/­datastore/­docshbase.apache.org/­book.htmlprometheus.io/­docs
DeveloperAtos Convergence CreatorsGoogleApache Software Foundation infoApache top-level project, originally developed by Powerset
Initial release2016200820082015
Current release17032.3.4, January 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache version 2Open Source infoApache 2.0
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 languageJavaJavaGo
Server operating systemsLinuxhostedLinux
Unix
Windows infousing Cygwin
Linux
Windows
Data schemeSchema and schema-less with LDAP viewsschema-freeschema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateoptionalyes, details hereoptions to bring your own types, AVRONumeric data only
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.yesnonono infoImport of XML data possible
Secondary indexesyesyesnono
SQL infoSupport of SQLnoSQL-like query language (GQL)nono
APIs and other access methodsLDAPgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
RESTful HTTP/JSON API
Supported programming languagesAll languages with LDAP bindings.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresnousing Google App Engineyes infoCoprocessors in Javano
TriggersyesCallbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using PaxosMulti-source replication
Source-replica replication
yes infoby Federation
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyesno
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.Immediate Consistency or Eventual Consistencynone
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
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 TransactionsSingle row ACID (across millions of columns)no
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.yesnoyesno
User concepts infoAccess controlLDAP bind authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACno

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More resources
Atos Standard Common RepositoryGoogle Cloud DatastoreHBasePrometheus
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