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DBMS > Google Cloud Datastore vs. Hawkular Metrics vs. Microsoft Azure Table Storage vs. OrigoDB vs. STSdb

System Properties Comparison Google Cloud Datastore vs. Hawkular Metrics vs. Microsoft Azure Table Storage vs. OrigoDB vs. STSdb

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonOrigoDB  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionAutomatically 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 Wide Column Store for rapid development using massive semi-structured datasetsA fully ACID in-memory object graph databaseKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelDocument storeTime Series DBMSWide column storeDocument store
Object oriented DBMS
Key-value store
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
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Websitecloud.google.com/­datastorewww.hawkular.orgazure.microsoft.com/­en-us/­services/­storage/­tablesorigodb.comgithub.com/­STSSoft/­STSdb4
Technical documentationcloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guideorigodb.com/­docs
DeveloperGoogleCommunity supported by Red HatMicrosoftRobert Friberg et alSTS Soft SC
Initial release2008201420122009 infounder the name LiveDB2011
Current release4.0.8, September 2015
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen SourceOpen Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC#C#
Server operating systemshostedLinux
OS X
Windows
hostedLinux
Windows
Windows
Data schemeschema-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyesUser defined using .NET types and collectionsyes infoprimitive types and user defined types (classes)
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.nononono infocan be achieved using .NET
Secondary indexesyesnonoyesno
SQL infoSupport of SQLSQL-like query language (GQL)nononono
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTRESTful HTTP API.NET Client API
HTTP API
LINQ
.NET Client API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.NetC#
Java
Server-side scripts infoStored proceduresusing Google App Enginenonoyesno
TriggersCallbacks using the Google Apps Engineyes infovia Hawkular Alertingnoyes infoDomain Eventsno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraSharding infoImplicit feature of the cloud servicehorizontal partitioning infoclient side managed; servers are not synchronizednone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factor infobased on Cassandrayes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 integrityyes infovia ReferenceProperties or Ancestor pathsnonodepending on modelno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnooptimistic lockingACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights based on private key authentication or shared access signaturesRole based authorizationno

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More resources
Google Cloud DatastoreHawkular MetricsMicrosoft Azure Table StorageOrigoDBSTSdb
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