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

System Properties Comparison Amazon Aurora vs. Netezza vs. PouchDB vs. Realm 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 comparisonRealm  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 DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSDocument storeDocument storeRelational DBMS
Secondary database modelsDocument store
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
Score7.41
Rank#52  Overall
#8  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­rds/­aurorawww.ibm.com/­products/­netezzapouchdb.comrealm.iospark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlpouchdb.com/­guidesrealm.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonIBMApache Software FoundationRealm, acquired by MongoDB in May 2019Apache Software Foundation
Initial release20152000201220142014
Current release7.1.1, June 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen SourceOpen SourceOpen 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 languageJavaScriptScala
Server operating systemshostedLinux infoincluded in applianceserver-less, requires a JavaScript environment (browser, Node.js)Android
Backend: server-less
iOS
Windows
Linux
OS X
Windows
Data schemeyesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyesyes
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.yesnonono
Secondary indexesyesyesyes infovia viewsyesno
SQL infoSupport of SQLyesyesnonoSQL-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
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
Java infowith Android only
Objective-C
React Native
Swift
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesyesView functions in JavaScriptno inforuns within the applications so server-side scripts are unnecessaryno
Triggersyesnoyesyes infoChange Listenersno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding infowith a proxy-based framework, named couchdb-loungenoneyes, 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
nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.yesyesyes infoIn-Memory realmno
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 IBMPouchDBRealmSpark SQL
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