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DBMS > Amazon Aurora vs. Apache Impala vs. Interbase vs. Oracle Berkeley DB vs. Splice Machine

System Properties Comparison Amazon Aurora vs. Apache Impala vs. Interbase vs. Oracle Berkeley DB vs. Splice Machine

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Impala  Xexclude from comparisonInterbase  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAnalytic DBMS for HadoopLight-weight proven RDBMS infooriginally from BorlandWidely used in-process key-value storeOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMSRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational 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
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteaws.amazon.com/­rds/­auroraimpala.apache.orgwww.embarcadero.com/­products/­interbasewww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlsplicemachine.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlimpala.apache.org/­impala-docs.htmldocs.embarcadero.com/­products/­interbasedocs.oracle.com/­cd/­E17076_05/­html/­index.htmlsplicemachine.com/­how-it-works
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaEmbarcaderoOracle infooriginally developed by Sleepycat, which was acquired by OracleSplice Machine
Initial release20152013198419942014
Current release4.1.0, June 2022InterBase 2020, December 201918.1.40, May 20203.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source infocommercial license availableOpen 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++CC, Java, C++ (depending on the Berkeley DB edition)Java
Server operating systemshostedLinuxAndroid
iOS
Linux
OS X
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
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 possibleyes infoonly with the Berkeley DB XML edition
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyesyes infoSQL interfaced based on SQLite is availableyes
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
ADO.NET
JDBC
ODBC
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
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
C#
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 languagenoyes infoJava
Triggersyesnoyesyes infoonly for the SQL APIyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingnonenoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factorInterbase Change ViewsSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMultiversion concurreny controlyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyesyes
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 ImpalaInterbaseOracle Berkeley DBSplice Machine
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