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DBMS > Netezza vs. Spark SQL vs. STSdb vs. TDSQL for MySQL

System Properties Comparison Netezza vs. Spark SQL vs. STSdb vs. TDSQL for MySQL

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Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsSpark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodA high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.
Primary database modelRelational DBMSRelational DBMSKey-value storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.18
Rank#46  Overall
#29  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.06
Rank#365  Overall
#55  Key-value stores
Score0.82
Rank#213  Overall
#97  Relational DBMS
Websitewww.ibm.com/­products/­netezzaspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4www.tencentcloud.com/­products/­dcdb
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.tencentcloud.com/­document/­product/­1042
DeveloperIBMApache Software FoundationSTS Soft SCTencent
Initial release2000201420112013
Current release3.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoGPLv2, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC#
Server operating systemsLinux infoincluded in applianceLinux
OS X
Windows
Windowshosted
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyes infoprimitive types and user defined types (classes)yes
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 indexesyesnonoyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsnoyes
APIs and other access methodsJDBC
ODBC
OLE DB
JDBC
ODBC
.NET Client APIJDBC
ODBC
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
Java
Python
R
Scala
C#
Java
C
C#
C++
Java
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesnonoyes
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CorenoneAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnonenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
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.nono
User concepts infoAccess controlUsers with fine-grained authorization conceptnonoUsers with fine-grained authorization concept

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More resources
Netezza infoAlso called PureData System for Analytics by IBMSpark SQLSTSdbTDSQL for MySQL
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