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DBMS > Microsoft Azure AI Search vs. NSDb vs. Spark SQL vs. VictoriaMetrics

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

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Editorial information provided by DB-Engines
NameMicrosoft Azure AI Search  Xexclude from comparisonNSDb  Xexclude from comparisonSpark SQL  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionSearch-as-a-service for web and mobile app developmentScalable, 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 processingA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelSearch engineTime Series DBMSRelational DBMSTime Series 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
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.32
Rank#162  Overall
#14  Time Series DBMS
Websiteazure.microsoft.com/­en-us/­services/­searchnsdb.iospark.apache.org/­sqlvictoriametrics.com
Technical documentationlearn.microsoft.com/­en-us/­azure/­searchnsdb.io/­Architecturespark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperMicrosoftApache Software FoundationVictoriaMetrics
Initial release2015201720142018
Current releaseV13.5.0 ( 2.13), September 2023v1.91, May 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ScalaScalaGo
Server operating systemshostedLinux
macOS
Linux
OS X
Windows
FreeBSD
Linux
macOS
OpenBSD
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyes: 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 indexesyesall fields are automatically indexedno
SQL infoSupport of SQLnoSQL-like query languageSQL-like DML and DDL statementsno
APIs and other access methodsRESTful HTTP APIgRPC
HTTP REST
WebSocket
JDBC
ODBC
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesC#
Java
JavaScript
Python
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 serviceShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud servicenoneSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesUsing Apache Luceneyesyes
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 authenticationno

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More resources
Microsoft Azure AI SearchNSDbSpark SQLVictoriaMetrics
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