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DBMS > Google BigQuery vs. Microsoft SQL Server vs. Netezza vs. Sqrrl

System Properties Comparison Google BigQuery vs. Microsoft SQL Server vs. Netezza vs. Sqrrl

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionLarge scale data warehouse service with append-only tablesMicrosofts flagship relational DBMSData warehouse and analytics appliance part of IBM PureSystemsAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelRelational DBMSRelational DBMSRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score60.38
Rank#19  Overall
#13  Relational DBMS
Score824.29
Rank#3  Overall
#3  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Websitecloud.google.com/­bigquerywww.microsoft.com/­en-us/­sql-serverwww.ibm.com/­products/­netezzasqrrl.com
Technical documentationcloud.google.com/­bigquery/­docslearn.microsoft.com/­en-US/­sql/­sql-server
DeveloperGoogleMicrosoftIBMAmazon infooriginally Sqrrl Data, Inc.
Initial release2010198920002012
Current releaseSQL Server 2022, November 2022
License infoCommercial or Open Sourcecommercialcommercial inforestricted free version is availablecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java
Server operating systemshostedLinux
Windows
Linux infoincluded in applianceLinux
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesnoyesyesyes
SQL infoSupport of SQLyesyesyesno
APIs and other access methodsRESTful HTTP/JSON APIADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
JDBC
ODBC
OLE DB
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
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
C
C++
Fortran
Java
Lua
Perl
Python
R
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javayesno
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesnonetables can be distributed across several files (horizontal partitioning); sharding through federationShardingSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesyes, but depending on the SQL-Server EditionSource-replica replicationselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying dataACIDACIDAtomic updates per row, document, or graph entity
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.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-standardUsers with fine-grained authorization conceptCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
Google BigQueryMicrosoft SQL ServerNetezza infoAlso called PureData System for Analytics by IBMSqrrl
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