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DBMS > Atos Standard Common Repository vs. Google Cloud Datastore vs. Hawkular Metrics vs. SWC-DB vs. Valentina Server

System Properties Comparison Atos Standard Common Repository vs. Google Cloud Datastore vs. Hawkular Metrics vs. SWC-DB vs. Valentina Server

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparisonValentina Server  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 PlatformHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A high performance, scalable Wide Column DBMSObject-relational database and reports server
Primary database modelDocument store
Key-value store
Document storeTime Series DBMSWide column storeRelational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score0.01
Rank#376  Overall
#13  Wide column stores
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorycloud.google.com/­datastorewww.hawkular.orggithub.com/­kashirin-alex/­swc-db
www.swcdb.org
www.valentina-db.net
Technical documentationcloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidevalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperAtos Convergence CreatorsGoogleCommunity supported by Red HatAlex KashirinParadigma Software
Initial release20162008201420201999
Current release17030.5, April 20215.7.5
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoGPL V3commercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC++
Server operating systemsLinuxhostedLinux
OS X
Windows
LinuxLinux
OS X
Windows
Data schemeSchema and schema-less with LDAP viewsschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateoptionalyes, details hereyesyes
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
Secondary indexesyesyesnoyes
SQL infoSupport of SQLnoSQL-like query language (GQL)noSQL-like query languageyes
APIs and other access methodsLDAPgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTProprietary protocol
Thrift
ODBC
Supported programming languagesAll languages with LDAP bindings.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
C++.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresnousing Google App Enginenonoyes
TriggersyesCallbacks using the Google Apps Engineyes infovia Hawkular Alertingnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingSharding infobased on CassandraSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using Paxosselectable replication factor infobased on Cassandra
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 infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyes
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 Transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesnononoyes
User concepts infoAccess controlLDAP bind authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nofine grained access rights according to SQL-standard

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More resources
Atos Standard Common RepositoryGoogle Cloud DatastoreHawkular MetricsSWC-DB infoSuper Wide Column DatabaseValentina Server
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