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DBMS > Microsoft Azure Data Explorer vs. NSDb vs. OrigoDB vs. VictoriaMetrics

System Properties Comparison Microsoft Azure Data Explorer vs. NSDb vs. OrigoDB vs. VictoriaMetrics

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Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonNSDb  Xexclude from comparisonOrigoDB  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesA fully ACID in-memory object graph databaseA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelRelational DBMS infocolumn orientedTime Series DBMSDocument store
Object oriented DBMS
Time Series DBMS
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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.16
Rank#69  Overall
#37  Relational DBMS
Score0.00
Rank#396  Overall
#42  Time Series DBMS
Score0.03
Rank#378  Overall
#51  Document stores
#18  Object oriented DBMS
Score1.42
Rank#161  Overall
#14  Time Series DBMS
Websiteazure.microsoft.com/­services/­data-explorernsdb.ioorigodb.comvictoriametrics.com
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorernsdb.io/­Architectureorigodb.com/­docsdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperMicrosoftRobert Friberg et alVictoriaMetrics
Initial release201920172009 infounder the name LiveDB2018
Current releasecloud service with continuous releasesv1.91, May 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open SourceOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ScalaC#Go
Server operating systemshostedLinux
macOS
Linux
Windows
FreeBSD
Linux
macOS
OpenBSD
Data schemeFixed schema with schema-less datatypes (dynamic)yes
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-typesyes: int, bigint, decimal, stringUser defined using .NET types and collections
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 infocan be achieved using .NETno
Secondary indexesall fields are automatically indexedall fields are automatically indexedyes
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetSQL-like query languagenono
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
gRPC
HTTP REST
WebSocket
.NET Client API
HTTP API
LINQ
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Scala
.Net
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, Rnoyesno
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoDomain Eventsno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardinghorizontal partitioning infoclient side managed; servers are not synchronized
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynonodepending on modelno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesUsing Apache Luceneyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAzure Active Directory AuthenticationRole based authorization

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More resources
Microsoft Azure Data ExplorerNSDbOrigoDBVictoriaMetrics
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