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

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

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHBase  Xexclude from comparisonMicrosoft Azure Table Storage  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.Wide-column store based on Apache Hadoop and on concepts of BigTableA Wide Column Store for rapid development using massive semi-structured datasetsKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelDocument storeTime Series DBMSWide column storeWide column storeKey-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
Score30.50
Rank#26  Overall
#2  Wide column stores
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.04
Rank#360  Overall
#52  Key-value stores
Websitecloud.google.com/­datastorewww.hawkular.orghbase.apache.orgazure.microsoft.com/­en-us/­services/­storage/­tablesgithub.com/­STSSoft/­STSdb4
Technical documentationcloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidehbase.apache.org/­book.html
DeveloperGoogleCommunity supported by Red HatApache Software Foundation infoApache top-level project, originally developed by PowersetMicrosoftSTS Soft SC
Initial release20082014200820122011
Current release2.3.4, January 20214.0.8, September 2015
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache version 2commercialOpen Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC#
Server operating systemshostedLinux
OS X
Windows
Linux
Unix
Windows infousing Cygwin
hostedWindows
Data schemeschema-freeschema-freeschema-free, schema definition possibleschema-freeyes
Typing infopredefined data types such as float or dateyes, details hereyesoptions to bring your own types, AVROyesyes 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
Secondary indexesyesnononono
SQL infoSupport of SQLSQL-like query language (GQL)nononono
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTJava API
RESTful HTTP API
Thrift
RESTful HTTP API.NET Client API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
Java
Server-side scripts infoStored proceduresusing Google App Enginenoyes infoCoprocessors in Javanono
TriggersCallbacks using the Google Apps Engineyes infovia Hawkular Alertingyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownoyesnono
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 or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoSingle row ACID (across millions of columns)optimistic lockingno
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.nonoyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights based on private key authentication or shared access signaturesno

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More resources
Google Cloud DatastoreHawkular MetricsHBaseMicrosoft Azure Table StorageSTSdb
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