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DBMS > Amazon Aurora vs. EXASOL vs. Spark SQL

System Properties Comparison Amazon Aurora vs. EXASOL vs. Spark SQL

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonEXASOL  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.50
Rank#49  Overall
#31  Relational DBMS
Score2.25
Rank#120  Overall
#57  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­rds/­aurorawww.exasol.comspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlwww.exasol.com/­resourcesspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonExasolApache Software Foundation
Initial release201520002014
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScala
Server operating systemshostedLinux
OS X
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.yesnono
Secondary indexesyesyesno
SQL infoSupport of SQLyesyesSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
.Net
JDBC
ODBC
WebSocket
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
Java
Lua
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesuser defined functionsno
Triggersyesyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoHadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
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.yesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardno

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More resources
Amazon AuroraEXASOLSpark SQL
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