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DBMS > Amazon Aurora vs. Netezza vs. PouchDB vs. Solr vs. Spark SQL

System Properties Comparison Amazon Aurora vs. Netezza vs. PouchDB vs. Solr vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonPouchDB  Xexclude from comparisonSolr  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonData warehouse and analytics appliance part of IBM PureSystemsJavaScript DBMS with an API inspired by CouchDBA widely used distributed, scalable search engine based on Apache LuceneSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSDocument storeSearch engineRelational DBMS
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.57
Rank#51  Overall
#32  Relational DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Score41.02
Rank#24  Overall
#3  Search engines
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­rds/­aurorawww.ibm.com/­products/­netezzapouchdb.comsolr.apache.orgspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlpouchdb.com/­guidessolr.apache.org/­resources.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonIBMApache Software FoundationApache Software FoundationApache Software Foundation
Initial release20152000201220062014
Current release7.1.1, June 20199.6.1, May 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen SourceOpen Source infoApache Version 2Open 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 languageJavaScriptJavaScala
Server operating systemshostedLinux infoincluded in applianceserver-less, requires a JavaScript environment (browser, Node.js)All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeyesyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesnoyes infosupports customizable data types and automatic typingyes
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.yesnoyesno
Secondary indexesyesyesyes infovia viewsyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLyesyesnoSolr Parallel SQL InterfaceSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
OLE DB
HTTP REST infoonly for PouchDB Server
JavaScript API
Java API
RESTful HTTP/JSON API
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++
Fortran
Java
Lua
Perl
Python
R
JavaScript.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesyesView functions in JavaScriptJava pluginsno
Triggersyesnoyesyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding infowith a proxy-based framework, named couchdb-loungeShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnooptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardUsers with fine-grained authorization conceptnoyesno

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More resources
Amazon AuroraNetezza infoAlso called PureData System for Analytics by IBMPouchDBSolrSpark SQL
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