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DBMS > Databricks vs. Google BigQuery vs. Microsoft SQL Server

System Properties Comparison Databricks vs. Google BigQuery vs. Microsoft SQL Server

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Large scale data warehouse service with append-only tablesMicrosofts flagship relational DBMS
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score63.94
Rank#18  Overall
#3  Document stores
#12  Relational DBMS
Score54.87
Rank#20  Overall
#14  Relational DBMS
Score920.09
Rank#3  Overall
#3  Relational DBMS
Websitedatabricks.comcloud.google.com/­bigquerywww.microsoft.com/­en-us/­sql-server
Technical documentationdatabricks.com/­documentationcloud.google.com/­bigquery/­docsdocs.microsoft.com/­en-US/­sql/­sql-server
DeveloperDatabricksGoogleMicrosoft
Initial release201320101989
Current releaseSQL Server 2022, November 2022
License infoCommercial or Open SourceOpen Sourcecommercialcommercial inforestricted free version is available
Cloud-based only infoOnly available as a cloud serviceyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++
Server operating systemshostedhostedLinux
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyes
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.yesnoyes
Secondary indexesyesnoyes
SQL infoSupport of SQLwith Databricks SQLyesyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP/JSON APIADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
Supported programming languagesPython
R
Scala
.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 and aggregatesuser 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 nodesyesyes, 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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoSince BigQuery is designed for querying dataACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
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
DatabricksGoogle BigQueryMicrosoft SQL Server
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