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DBMS > Microsoft Azure AI Search vs. Microsoft Azure Table Storage vs. NSDb vs. Spark SQL

System Properties Comparison Microsoft Azure AI Search vs. Microsoft Azure Table Storage vs. NSDb vs. Spark SQL

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Editorial information provided by DB-Engines
NameMicrosoft Azure AI Search  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonNSDb  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionSearch-as-a-service for web and mobile app developmentA Wide Column Store for rapid development using massive semi-structured datasetsScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelSearch engineWide column storeTime Series DBMSRelational DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.59
Rank#63  Overall
#7  Search engines
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteazure.microsoft.com/­en-us/­services/­searchazure.microsoft.com/­en-us/­services/­storage/­tablesnsdb.iospark.apache.org/­sql
Technical documentationlearn.microsoft.com/­en-us/­azure/­searchnsdb.io/­Architecturespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMicrosoftMicrosoftApache Software Foundation
Initial release2015201220172014
Current releaseV13.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ScalaScala
Server operating systemshostedhostedLinux
macOS
Linux
OS X
Windows
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes: int, bigint, decimal, stringyes
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.nononono
Secondary indexesyesnoall fields are automatically indexedno
SQL infoSupport of SQLnonoSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIRESTful HTTP APIgRPC
HTTP REST
WebSocket
JDBC
ODBC
Supported programming languagesC#
Java
JavaScript
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresnononono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding infoImplicit feature of the cloud serviceShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesUsing Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlyes infousing Azure authenticationAccess rights based on private key authentication or shared access signaturesno

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More resources
Microsoft Azure AI SearchMicrosoft Azure Table StorageNSDbSpark SQL
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