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DBMS > Amazon Aurora vs. Apache HBase vs. Apache Spark (SQL)

System Properties Comparison Amazon Aurora vs. Apache HBase vs. Apache Spark (SQL)

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache HBase  Xexclude from comparisonApache Spark (SQL)  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonWide-column store based on Apache Hadoop and on concepts of BigTableApache Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSWide column storeRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.48
Rank#45  Overall
#28  Relational DBMS
Score25.00
Rank#26  Overall
#2  Wide column stores
Score17.39
Rank#32  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­rds/­aurorahbase.apache.orgspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlhbase.apache.org/­book.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation
Initial release201520082014
Current release2.3.4, January 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open 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 languageJavaScala
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
Linux
OS X
Windows
Data schemeyesschema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyes
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 indexesyesnono
SQL infoSupport of SQLyesnoSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
Java API
RESTful HTTP API
Thrift
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
C#
C++
Groovy
Java
PHP
Python
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesyes infoCoprocessors in Javano
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 replicationMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDSingle row ACID (across millions of columns)no
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 Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACno

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More resources
Amazon AuroraApache HBaseApache Spark (SQL)
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