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DBMS > Google BigQuery vs. Microsoft SQL Server

System Properties Comparison Google BigQuery vs. Microsoft SQL Server

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Our visitors often compare Google BigQuery and Microsoft SQL Server with Amazon Redshift, Snowflake and MySQL.

Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesMicrosofts flagship relational DBMS
Primary database modelRelational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score45.62
Rank#24  Overall
#16  Relational DBMS
Score944.81
Rank#3  Overall
#3  Relational DBMS
Websitecloud.google.com/­bigquerywww.microsoft.com/­en-us/­sql-server
Technical documentationcloud.google.com/­bigquery/­docsdocs.microsoft.com/­en-US/­sql/­sql-server
DeveloperGoogleMicrosoft
Initial release20101989
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 schemeyesyes
Typing infopredefined data types such as float or dateyesyes
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 indexesnoyes
SQL infoSupport of SQLyesyes
APIs and other access methodsRESTful HTTP/JSON APIADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Java
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodesnonetables can be distributed across several files (horizontal partitioning); sharding through federation
Replication methods infoMethods for redundantly storing data on multiple nodesyes, but depending on the SQL-Server Edition
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying dataACID
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 privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
Google BigQueryMicrosoft SQL Server
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