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

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

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Impala  Xexclude from comparisonHypertable  Xexclude from comparisonInterbase  Xexclude from comparisonSplice Machine  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAnalytic DBMS for HadoopAn open source BigTable implementation based on distributed file systems such as HadoopLight-weight proven RDBMS infooriginally from BorlandOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMSWide column storeRelational DBMSRelational 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
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteaws.amazon.com/­rds/­auroraimpala.apache.orgwww.embarcadero.com/­products/­interbasesplicemachine.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlimpala.apache.org/­impala-docs.htmldocs.embarcadero.com/­products/­interbasesplicemachine.com/­how-it-works
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaHypertable Inc.EmbarcaderoSplice Machine
Initial release20152013200919842014
Current release4.1.0, June 20220.9.8.11, March 2016InterBase 2020, December 20193.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoGNU version 3. Commercial license availablecommercialOpen 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++C++CJava
Server operating systemshostedLinuxLinux
OS X
Windows infoan inofficial Windows port is available
Android
iOS
Linux
OS X
Windows
Linux
OS X
Solaris
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.yesnono infoexport as XML data possible
Secondary indexesyesyesrestricted infoonly exact value or prefix value scansyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsnoyesyes
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
C++ API
Thrift
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/ODBCC++
Java
Perl
PHP
Python
Ruby
.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyesyes infouser defined functions and integration of map-reducenoyes infoInterbase procedure and trigger languageyes infoJava
Triggersyesnonoyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factorselectable replication factor on file system levelInterbase Change ViewsMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceyesnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes 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.yesnoyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosnofine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon AuroraApache ImpalaHypertableInterbaseSplice Machine
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