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DBMS > Google Cloud Datastore vs. Microsoft Azure AI Search vs. mSQL vs. OrigoDB vs. Spark SQL

System Properties Comparison Google Cloud Datastore vs. Microsoft Azure AI Search vs. mSQL vs. OrigoDB vs. Spark SQL

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonOrigoDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformSearch-as-a-service for web and mobile app developmentmSQL (Mini SQL) is a simple and lightweight RDBMSA fully ACID in-memory object graph databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeSearch engineRelational DBMSDocument store
Object oriented DBMS
Relational DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score5.59
Rank#63  Overall
#7  Search engines
Score1.27
Rank#167  Overall
#77  Relational DBMS
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitecloud.google.com/­datastoreazure.microsoft.com/­en-us/­services/­searchhughestech.com.au/­products/­msqlorigodb.comspark.apache.org/­sql
Technical documentationcloud.google.com/­datastore/­docslearn.microsoft.com/­en-us/­azure/­searchorigodb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGoogleMicrosoftHughes TechnologiesRobert Friberg et alApache Software Foundation
Initial release2008201519942009 infounder the name LiveDB2014
Current releaseV14.4, October 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree licenses can be providedOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC#Scala
Server operating systemshostedhostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Linux
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyesUser defined using .NET types and collectionsyes
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 .NETno
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLSQL-like query language (GQL)noA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersnoSQL-like DML and DDL statements
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP APIJDBC
ODBC
.NET Client API
HTTP API
LINQ
JDBC
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
Java
JavaScript
Python
C
C++
Delphi
Java
Perl
PHP
Tcl
.NetJava
Python
R
Scala
Server-side scripts infoStored proceduresusing Google App Enginenonoyesno
TriggersCallbacks using the Google Apps Enginenonoyes infoDomain Eventsno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicenonehorizontal partitioning infoclient side managed; servers are not synchronizedyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes infoImplicit feature of the cloud servicenoneSource-replica replicationnone
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.Immediate Consistencynone
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 TransactionsnonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesnoyesyes
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.nononoyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes infousing Azure authenticationnoRole based authorizationno

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More resources
Google Cloud DatastoreMicrosoft Azure AI SearchmSQL infoMini SQLOrigoDBSpark SQL
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