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DBMS > Amazon Aurora vs. BigObject vs. Kinetica vs. Microsoft SQL Server vs. Spark SQL

System Properties Comparison Amazon Aurora vs. BigObject vs. Kinetica vs. Microsoft SQL Server vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonBigObject  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAnalytic DBMS for real-time computations and queriesFully vectorized database across both GPUs and CPUsMicrosofts flagship relational DBMSSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeSpatial DBMS
Time Series DBMS
Document store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score824.29
Rank#3  Overall
#3  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­rds/­aurorabigobject.iowww.kinetica.comwww.microsoft.com/­en-us/­sql-serverspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldocs.bigobject.iodocs.kinetica.comlearn.microsoft.com/­en-US/­sql/­sql-serverspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonBigObject, Inc.KineticaMicrosoftApache Software Foundation
Initial release20152015201219892014
Current release7.1, August 2021SQL Server 2022, November 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availablecommercialcommercial inforestricted free version is availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C++Scala
Server operating systemshostedLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
LinuxLinux
Windows
Linux
OS X
Windows
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.yesnonoyesno
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLyesSQL-like DML and DDL statementsSQL-like DML and DDL statementsyesSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
fluentd
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
JDBC
ODBC
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C++
Java
JavaScript (Node.js)
Python
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesLuauser defined functionsTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javano
Triggersyesnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnoneShardingtables can be distributed across several files (horizontal partitioning); sharding through federationyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneSource-replica replicationyes, but depending on the SQL-Server Editionnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesyes infoautomatically between fact table and dimension tablesyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infoGPU vRAM or System RAMyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardnoAccess rights for users and roles on table levelfine grained access rights according to SQL-standardno

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More resources
Amazon AuroraBigObjectKineticaMicrosoft SQL ServerSpark SQL
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