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DBMS > Amazon Aurora vs. Apache Impala vs. Google Cloud Spanner vs. Microsoft SQL Server

System Properties Comparison Amazon Aurora vs. Apache Impala vs. Google Cloud Spanner vs. Microsoft SQL Server

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Impala  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAnalytic DBMS for HadoopA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Microsofts flagship relational DBMS
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeDocument storeDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.05
Rank#49  Overall
#31  Relational DBMS
Score15.06
Rank#39  Overall
#24  Relational DBMS
Score3.37
Rank#97  Overall
#50  Relational DBMS
Score845.81
Rank#3  Overall
#3  Relational DBMS
Websiteaws.amazon.com/­rds/­auroraimpala.apache.orgcloud.google.com/­spannerwww.microsoft.com/­en-us/­sql-server
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlimpala.apache.org/­impala-docs.htmlcloud.google.com/­spanner/­docslearn.microsoft.com/­en-US/­sql/­sql-server
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleMicrosoft
Initial release2015201320171989
Current release4.1.0, June 2022SQL Server 2022, November 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialcommercial inforestricted free version is available
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++
Server operating systemshostedLinuxhostedLinux
Windows
Data schemeyesyesyesyes
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.yesnonoyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyes infoQuery statements complying to ANSI 2011yes
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
All languages supporting JDBC/ODBCGo
Java
JavaScript (Node.js)
Python
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
Server-side scripts infoStored proceduresyesyes infouser defined functions and integration of map-reducenoTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Java
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingtables can be distributed across several files (horizontal partitioning); sharding through federation
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factorMulti-source replication with 3 replicas for regional instances.yes, but depending on the SQL-Server Edition
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoStrict serializable isolationACID
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.yesnonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess 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
Amazon AuroraApache ImpalaGoogle Cloud SpannerMicrosoft SQL Server
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