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DBMS > Google Cloud Datastore vs. Hawkular Metrics vs. Kinetica vs. Microsoft Azure AI Search

System Properties Comparison Google Cloud Datastore vs. Hawkular Metrics vs. Kinetica vs. Microsoft Azure AI Search

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure AI Search  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.Fully vectorized database across both GPUs and CPUsSearch-as-a-service for web and mobile app development
Primary database modelDocument storeTime Series DBMSRelational DBMSSearch engine
Secondary database modelsSpatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score5.52
Rank#59  Overall
#6  Search engines
Websitecloud.google.com/­datastorewww.hawkular.orgwww.kinetica.comazure.microsoft.com/­en-us/­services/­search
Technical documentationcloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.kinetica.comlearn.microsoft.com/­en-us/­azure/­search
DeveloperGoogleCommunity supported by Red HatKineticaMicrosoft
Initial release2008201420122015
Current release7.1, August 2021V1
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyes
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
Linuxhosted
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyes, 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.nononono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like query language (GQL)noSQL-like DML and DDL statementsno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTJDBC
ODBC
RESTful HTTP API
RESTful HTTP API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
C#
Java
JavaScript
Python
Server-side scripts infoStored proceduresusing Google App Enginenouser defined functionsno
TriggersCallbacks using the Google Apps Engineyes infovia Hawkular Alertingyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factor infobased on CassandraSource-replica replicationyes infoImplicit feature of the cloud service
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 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 Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnonono
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.nonoyes infoGPU vRAM or System RAMno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights for users and roles on table levelyes infousing Azure authentication

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More resources
Google Cloud DatastoreHawkular MetricsKineticaMicrosoft Azure AI Search
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