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DBMS > Amazon Aurora vs. HBase vs. Spark SQL vs. STSdb

System Properties Comparison Amazon Aurora vs. HBase vs. Spark SQL vs. STSdb

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonHBase  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonWide-column store based on Apache Hadoop and on concepts of BigTableSpark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelRelational DBMSWide column storeRelational DBMSKey-value store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.05
Rank#49  Overall
#31  Relational DBMS
Score31.60
Rank#26  Overall
#2  Wide column stores
Score19.56
Rank#34  Overall
#21  Relational DBMS
Score0.13
Rank#344  Overall
#51  Key-value stores
Websiteaws.amazon.com/­rds/­aurorahbase.apache.orgspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
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 FoundationSTS Soft SC
Initial release2015200820142011
Current release2.3.4, January 20213.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open Source infoApache 2.0Open Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaC#
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
Linux
OS X
Windows
Windows
Data schemeyesschema-free, schema definition possibleyesyes
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesyes infoprimitive types and user defined types (classes)
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 indexesyesnonono
SQL infoSupport of SQLyesnoSQL-like DML and DDL statementsno
APIs and other access methodsADO.NET
JDBC
ODBC
Java API
RESTful HTTP API
Thrift
JDBC
ODBC
.NET Client API
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
C#
Java
Server-side scripts infoStored proceduresyesyes infoCoprocessors in Javanono
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDSingle row ACID (across millions of columns)nono
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.yesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnono

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More resources
Amazon AuroraHBaseSpark SQLSTSdb
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