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DBMS > Microsoft Azure Data Explorer vs. VictoriaMetrics vs. YottaDB

System Properties Comparison Microsoft Azure Data Explorer vs. VictoriaMetrics vs. YottaDB

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Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonVictoriaMetrics  Xexclude from comparisonYottaDB  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformA fast, cost-effective and scalable Time Series DBMS and monitoring solutionA fast and solid embedded Key-value store
Primary database modelRelational DBMS infocolumn orientedTime Series DBMSKey-value store
Secondary database modelsDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
Relational DBMS infousing the Octo plugin
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score1.32
Rank#162  Overall
#14  Time Series DBMS
Score0.20
Rank#317  Overall
#47  Key-value stores
Websiteazure.microsoft.com/­services/­data-explorervictoriametrics.comyottadb.com
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
yottadb.com/­resources/­documentation
DeveloperMicrosoftVictoriaMetricsYottaDB, LLC
Initial release201920182001
Current releasecloud service with continuous releasesv1.91, May 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoAGPL 3.0
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 languageGoC
Server operating systemshostedFreeBSD
Linux
macOS
OpenBSD
Docker
Linux
Data schemeFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesno
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.yesnono
Secondary indexesall fields are automatically indexedno
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetnoby using the Octo plugin
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
PostgreSQL wire protocol infousing the Octo plugin
Proprietary protocol
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, Rno
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Synchronous replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyes
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.nonoyes
User concepts infoAccess controlAzure Active Directory AuthenticationUsers and groups based on OS-security mechanisms

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More resources
Microsoft Azure Data ExplorerVictoriaMetricsYottaDB
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