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DBMS > Microsoft Azure Table Storage vs. Netezza vs. Spark SQL vs. STSdb

System Properties Comparison Microsoft Azure Table Storage vs. Netezza vs. Spark SQL vs. STSdb

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Editorial information provided by DB-Engines
NameMicrosoft Azure Table Storage  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionA Wide Column Store for rapid development using massive semi-structured datasetsData 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 method
Primary database modelWide column storeRelational DBMSRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.92
Rank#73  Overall
#6  Wide column stores
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
Websiteazure.microsoft.com/­en-us/­services/­storage/­tableswww.ibm.com/­products/­netezzaspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMicrosoftIBMApache Software FoundationSTS Soft SC
Initial release2012200020142011
Current release3.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC#
Server operating systemshostedLinux infoincluded in applianceLinux
OS X
Windows
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes infoprimitive types and user defined types (classes)
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 indexesnoyesnono
SQL infoSupport of SQLnoyesSQL-like DML and DDL statementsno
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
OLE DB
JDBC
ODBC
.NET Client API
Supported programming languages.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Fortran
Java
Lua
Perl
Python
R
Java
Python
R
Scala
C#
Java
Server-side scripts infoStored proceduresnoyesnono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
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 dataoptimistic lockingACIDnono
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 controlAccess rights based on private key authentication or shared access signaturesUsers with fine-grained authorization conceptnono

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More resources
Microsoft Azure Table StorageNetezza infoAlso called PureData System for Analytics by IBMSpark SQLSTSdb
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