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DBMS > Microsoft Azure Table Storage vs. Spark SQL vs. VictoriaMetrics

System Properties Comparison Microsoft Azure Table Storage vs. Spark SQL vs. VictoriaMetrics

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Editorial information provided by DB-Engines
NameMicrosoft Azure Table Storage  Xexclude from comparisonSpark SQL  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionA Wide Column Store for rapid development using massive semi-structured datasetsSpark 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 modelWide column storeRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.92
Rank#73  Overall
#6  Wide column stores
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score1.42
Rank#161  Overall
#14  Time Series DBMS
Websiteazure.microsoft.com/­en-us/­services/­storage/­tablesspark.apache.org/­sqlvictoriametrics.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperMicrosoftApache Software FoundationVictoriaMetrics
Initial release201220142018
Current release3.5.0 ( 2.13), September 2023v1.91, May 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaGo
Server operating systemshostedLinux
OS X
Windows
FreeBSD
Linux
macOS
OpenBSD
Data schemeschema-freeyes
Typing infopredefined data types such as float or dateyesyes
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.nonono
Secondary indexesnono
SQL infoSupport of SQLnoSQL-like DML and DDL statementsno
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languages.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlAccess rights based on private key authentication or shared access signaturesno

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More resources
Microsoft Azure Table StorageSpark SQLVictoriaMetrics
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