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

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

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Druid  Xexclude from comparisonApache Impala  Xexclude from comparisonInterbase  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAnalytic DBMS for 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 DBMS
Time Series DBMS
Relational DBMSRelational 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
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series 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/­auroradruid.apache.orgimpala.apache.orgwww.embarcadero.com/­products/­interbasesplicemachine.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldruid.apache.org/­docs/­latest/­designimpala.apache.org/­impala-docs.htmldocs.embarcadero.com/­products/­interbasesplicemachine.com/­how-it-works
DeveloperAmazonApache Software Foundation and contributorsApache Software Foundation infoApache top-level project, originally developed by ClouderaEmbarcaderoSplice Machine
Initial release20152012201319842014
Current release29.0.1, April 20244.1.0, June 2022InterBase 2020, December 20193.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache license v2Open Source infoApache Version 2commercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++CJava
Server operating systemshostedLinux
OS X
Unix
LinuxAndroid
iOS
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyes infoschema-less columns are supportedyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 infoexport as XML data possible
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLyesSQL for queryingSQL-like DML and DDL statementsyesyes
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
RESTful HTTP/JSON API
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
Clojure
JavaScript
PHP
Python
R
Ruby
Scala
All languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyesnoyes infouser defined functions and integration of map-reduceyes infoInterbase procedure and trigger languageyes infoJava
Triggersyesnonoyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infomanual/auto, time-basedShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes, via HDFS, S3 or other storage enginesselectable replication factorInterbase Change ViewsMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoquery execution via MapReducenoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual 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.yesnonoyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine 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 DruidApache ImpalaInterbaseSplice Machine
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