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

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

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonKingbase  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonPouchDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAn enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.Data warehouse and analytics appliance part of IBM PureSystemsJavaScript DBMS with an API inspired by CouchDBSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSRelational DBMSDocument storeRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.57
Rank#51  Overall
#32  Relational DBMS
Score0.50
Rank#257  Overall
#119  Relational DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­rds/­aurorawww.kingbase.com.cnwww.ibm.com/­products/­netezzapouchdb.comspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlpouchdb.com/­guidesspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonBeiJing KINGBASE Information technologies inc.IBMApache Software FoundationApache Software Foundation
Initial release20151999200020122014
Current releaseV8.0, August 20217.1.1, June 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen 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 languageC and JavaJavaScriptScala
Server operating systemshostedLinux
Windows
Linux infoincluded in applianceserver-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Windows
Data schemeyesyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.yesyesnono
Secondary indexesyesyesyesyes infovia viewsno
SQL infoSupport of SQLyesStandard with numerous extensionsyesnoSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT
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
.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
JavaScriptJava
Python
R
Scala
Server-side scripts infoStored proceduresyesuser defined functionsyesView functions in JavaScriptno
Triggersyesyesnoyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioninghorizontal partitioning (by range, list and hash) and vertical partitioningShardingSharding infowith a proxy-based framework, named couchdb-loungeyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesSource-replica replicationMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.yesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardUsers with fine-grained authorization conceptnono

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More resources
Amazon AuroraKingbaseNetezza infoAlso called PureData System for Analytics by IBMPouchDBSpark SQL
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