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DBMS > Amazon Aurora vs. Citus vs. PouchDB vs. Solr

System Properties Comparison Amazon Aurora vs. Citus vs. PouchDB vs. Solr

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonCitus  Xexclude from comparisonPouchDB  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLJavaScript DBMS with an API inspired by CouchDBA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSRelational DBMSDocument storeSearch engine
Secondary database modelsDocument storeDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score2.28
Rank#115  Overall
#21  Document stores
Score42.91
Rank#24  Overall
#3  Search engines
Websiteaws.amazon.com/­rds/­aurorawww.citusdata.compouchdb.comsolr.apache.org
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldocs.citusdata.compouchdb.com/­guidessolr.apache.org/­resources.html
DeveloperAmazonApache Software FoundationApache Software Foundation
Initial release2015201020122006
Current release8.1, December 20187.1.1, June 20199.6.0, April 2024
License infoCommercial or Open SourcecommercialOpen Source infoAGPL, commercial license also availableOpen SourceOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJavaScriptJava
Server operating systemshostedLinuxserver-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)
Data schemeyesyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesnoyes infosupports customizable data types and automatic typing
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.yesyes infospecific XML type available, but no XML query functionalitynoyes
Secondary indexesyesyesyes infovia viewsyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesyes infostandard, with numerous extensionsnoSolr Parallel SQL Interface
APIs and other access methodsADO.NET
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP REST infoonly for PouchDB Server
JavaScript API
Java API
RESTful HTTP/JSON 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
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
JavaScript.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.View functions in JavaScriptJava plugins
Triggersyesyesyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding infowith a proxy-based framework, named couchdb-loungeSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardnoyes

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More resources
Amazon AuroraCitusPouchDBSolr
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