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DBMS > Amazon Aurora vs. Apache Druid vs. Netezza vs. Quasardb vs. Splice Machine

System Properties Comparison Amazon Aurora vs. Apache Druid vs. Netezza vs. Quasardb vs. Splice Machine

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Druid  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonQuasardb  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 dataData warehouse and analytics appliance part of IBM PureSystemsDistributed, high-performance timeseries databaseOpen-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 DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteaws.amazon.com/­rds/­auroradruid.apache.orgwww.ibm.com/­products/­netezzaquasar.aisplicemachine.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldruid.apache.org/­docs/­latest/­designdoc.quasar.ai/­mastersplicemachine.com/­how-it-works
DeveloperAmazonApache Software Foundation and contributorsIBMquasardbSplice Machine
Initial release20152012200020092014
Current release29.0.1, April 20243.14.1, January 20243.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache license v2commercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen 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 languageJavaC++Java
Server operating systemshostedLinux
OS X
Unix
Linux infoincluded in applianceBSD
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyes infoschema-less columns are supportedyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes infointeger and binaryyes
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
Secondary indexesyesyesyesyes infowith tagsyes
SQL infoSupport of SQLyesSQL for queryingyesSQL-like query languageyes
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
RESTful HTTP/JSON API
JDBC
ODBC
OLE DB
HTTP APIJDBC
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
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyesnoyesnoyes infoJava
Triggersyesnononoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infomanual/auto, time-basedShardingSharding infoconsistent hashingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes, via HDFS, S3 or other storage enginesSource-replica replicationSource-replica replication with selectable replication factorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyeswith Hadoop integrationYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoTransient modeyes
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 systemUsers with fine-grained authorization conceptCryptographically strong user authentication and audit trailAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon AuroraApache DruidNetezza infoAlso called PureData System for Analytics by IBMQuasardbSplice Machine
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