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DBMS > Apache Doris vs. Netezza vs. Spark SQL vs. Teradata

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

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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 comparisonTeradata  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 processingA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.57
Rank#244  Overall
#113  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitedoris.apache.org
github.com/­apache/­doris
www.ibm.com/­products/­netezzaspark.apache.org/­sqlwww.teradata.com
Technical documentationgithub.com/­apache/­doris/­wikispark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.teradata.com
DeveloperApache Software Foundation, originally contributed from BaiduIBMApache Software FoundationTeradata
Initial release2017200020141984
Current release1.2.2, February 20233.5.0 ( 2.13), September 2023Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScala
Server operating systemsLinuxLinux infoincluded in applianceLinux
OS X
Windows
hosted
Linux
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonoyes
Secondary indexesyesyesnoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLyesyesSQL-like DML and DDL statementsyes infoSQL 2016 + extensions
APIs and other access methodsJDBC
MySQL client
JDBC
ODBC
OLE DB
JDBC
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesJavaC
C++
Fortran
Java
Lua
Perl
Python
R
Java
Python
R
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresuser defined functionsyesnoyes infoUDFs, stored procedures, table functions in parallel
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingyes, utilizing Spark CoreSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardUsers with fine-grained authorization conceptnofine grained access rights according to SQL-standard

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More resources
Apache DorisNetezza infoAlso called PureData System for Analytics by IBMSpark SQLTeradata
DB-Engines blog posts

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