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DBMS > Microsoft Azure AI Search vs. Sadas Engine vs. Spark SQL vs. VictoriaMetrics

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

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Editorial information provided by DB-Engines
NameMicrosoft Azure AI Search  Xexclude from comparisonSadas Engine  Xexclude from comparisonSpark SQL  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionSearch-as-a-service for web and mobile app developmentSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsSpark 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 engineRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.71
Rank#64  Overall
#8  Search engines
Score0.03
Rank#379  Overall
#156  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score1.42
Rank#161  Overall
#14  Time Series DBMS
Websiteazure.microsoft.com/­en-us/­services/­searchwww.sadasengine.comspark.apache.org/­sqlvictoriametrics.com
Technical documentationlearn.microsoft.com/­en-us/­azure/­searchwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperMicrosoftSADAS s.r.l.Apache Software FoundationVictoriaMetrics
Initial release2015200620142018
Current releaseV18.03.5.0 ( 2.13), September 2023v1.91, May 2023
License infoCommercial or Open Sourcecommercialcommercial infofree trial version availableOpen 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 languageC++ScalaGo
Server operating systemshostedAIX
Linux
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
OpenBSD
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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 indexesyesyesno
SQL infoSupport of SQLnoyesSQL-like DML and DDL statementsno
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Proprietary protocol
JDBC
ODBC
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesC#
Java
JavaScript
Python
.Net
C
C#
C++
Groovy
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnononono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicehorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud servicenonenoneSynchronous replication
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 integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
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.noyes infomanaged by 'Learn by Usage'nono
User concepts infoAccess controlyes infousing Azure authenticationAccess rights for users, groups and roles according to SQL-standardno

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More resources
Microsoft Azure AI SearchSadas EngineSpark SQLVictoriaMetrics
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