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DBMS > Google Cloud Datastore vs. Microsoft SQL Server

System Properties Comparison Google Cloud Datastore vs. Microsoft SQL Server

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMicrosofts flagship relational DBMS
Primary database modelDocument storeRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.84
Rank#76  Overall
#11  Document stores
Score944.81
Rank#3  Overall
#3  Relational DBMS
Websitecloud.google.com/­datastorewww.microsoft.com/­en-us/­sql-server
Technical documentationcloud.google.com/­datastore/­docsdocs.microsoft.com/­en-US/­sql/­sql-server
DeveloperGoogleMicrosoft
Initial release20081989
Current releaseSQL Server 2019, November 2019
License infoCommercial or Open Sourcecommercialcommercial inforestricted free version is available
Cloud-based only infoOnly available as a cloud serviceyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++
Server operating systemshostedLinux
Windows
Data schemeschema-freeyes
Typing infopredefined data types such as float or dateyes, details hereyes
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.noyes
Secondary indexesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)yes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
Server-side scripts infoStored proceduresusing Google App EngineTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Java
TriggersCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesShardingtables can be distributed across several files (horizontal partitioning); sharding through federation
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes, but depending on the SQL-Server Edition
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowno
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 Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreMicrosoft SQL Server
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