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DBMS > Apache Doris vs. Netezza vs. Spark SQL

System Properties Comparison Apache Doris vs. Netezza vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Doris  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn MPP-based analytics DBMS embracing the MySQL protocolData warehouse and analytics appliance part of IBM PureSystemsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.66
Rank#243  Overall
#115  Relational DBMS
Score16.79
Rank#40  Overall
#25  Relational DBMS
Score20.62
Rank#36  Overall
#22  Relational DBMS
Websitedoris.apache.org
github.com/­apache/­doris
www.ibm.com/­products/­netezzaspark.apache.org/­sql
Technical documentationgithub.com/­apache/­doris/­wikispark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation, originally contributed from BaiduIBMApache Software Foundation
Initial release201720002014
Current release0.14, May 20213.3.0 ( 2.13), June 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScala
Server operating systemsLinuxLinux infoincluded in applianceLinux
OS X
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.nono
Secondary indexesyesyesno
SQL infoSupport of SQLyesyesSQL-like DML and DDL statements
APIs and other access methodsJDBC
MySQL client
JDBC
ODBC
OLE DB
JDBC
ODBC
Supported programming languagesJavaC
C++
Fortran
Java
Lua
Perl
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyesno
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlfine grained access rights according to SQL-standardUsers with fine-grained authorization conceptno

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More resources
Apache DorisNetezza infoAlso called PureData System for Analytics by IBMSpark SQL
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