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DBMS > Amazon Aurora vs. Apache Impala vs. Interbase vs. PouchDB vs. Splice Machine

System Properties Comparison Amazon Aurora vs. Apache Impala vs. Interbase vs. PouchDB vs. Splice Machine

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Impala  Xexclude from comparisonInterbase  Xexclude from comparisonPouchDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAnalytic DBMS for HadoopLight-weight proven RDBMS infooriginally from BorlandJavaScript DBMS with an API inspired by CouchDBOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMSRelational DBMSDocument storeRelational DBMS
Secondary database modelsDocument storeDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.57
Rank#51  Overall
#32  Relational DBMS
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score4.08
Rank#75  Overall
#41  Relational DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteaws.amazon.com/­rds/­auroraimpala.apache.orgwww.embarcadero.com/­products/­interbasepouchdb.comsplicemachine.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlimpala.apache.org/­impala-docs.htmldocs.embarcadero.com/­products/­interbasepouchdb.com/­guidessplicemachine.com/­how-it-works
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaEmbarcaderoApache Software FoundationSplice Machine
Initial release20152013198420122014
Current release4.1.0, June 2022InterBase 2020, December 20197.1.1, June 20193.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen SourceOpen Source infoAGPL 3.0, commercial license available
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++CJavaScriptJava
Server operating systemshostedLinuxAndroid
iOS
Linux
OS X
Windows
server-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Solaris
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.yesnono infoexport as XML data possibleno
Secondary indexesyesyesyesyes infovia viewsyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyesnoyes
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
ADO.NET
JDBC
ODBC
HTTP REST infoonly for PouchDB Server
JavaScript API
JDBC
Native Spark Datasource
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
All languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
JavaScriptC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyesyes infouser defined functions and integration of map-reduceyes infoInterbase procedure and trigger languageView functions in JavaScriptyes infoJava
Triggersyesnoyesyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingnoneSharding infowith a proxy-based framework, named couchdb-loungeShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factorInterbase Change ViewsMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenoyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMultiversion concurreny controlyes, multi-version concurrency control (MVCC)
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.yesnoyesyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon AuroraApache ImpalaInterbasePouchDBSplice Machine
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