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DBMS > Microsoft Azure Data Explorer vs. OrigoDB vs. Spark SQL vs. StarRocks

System Properties Comparison Microsoft Azure Data Explorer vs. OrigoDB vs. Spark SQL vs. StarRocks

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Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonOrigoDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonStarRocks  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformA fully ACID in-memory object graph databaseSpark SQL is a component on top of 'Spark Core' for structured data processingAn open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics infoForked from Apache Doris
Primary database modelRelational DBMS infocolumn orientedDocument store
Object oriented DBMS
Relational DBMSRelational 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
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.06
Rank#380  Overall
#50  Document stores
#18  Object oriented DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.93
Rank#198  Overall
#93  Relational DBMS
Websiteazure.microsoft.com/­services/­data-explorerorigodb.comspark.apache.org/­sqlwww.starrocks.io
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerorigodb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.starrocks.io/­en-us/­latest/­introduction/­StarRocks_intro
DeveloperMicrosoftRobert Friberg et alApache Software FoundationThe Linux Foundation infosince Feb 2023
Initial release20192009 infounder the name LiveDB20142020
Current releasecloud service with continuous releases3.5.0 ( 2.13), September 20233.3, June 2024
License infoCommercial or Open SourcecommercialOpen SourceOpen 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

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Implementation languageC#ScalaC++, Java
Server operating systemshostedLinux
Windows
Linux
OS X
Windows
Linux
Data schemeFixed schema with schema-less datatypes (dynamic)yesyesyes
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-typesUser defined using .NET types and collectionsyesyes
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.yesno infocan be achieved using .NETnono
Secondary indexesall fields are automatically indexedyesnoyes
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetnoSQL-like DML and DDL statementsyes
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
.NET Client API
HTTP API
LINQ
JDBC
ODBC
JDBC
MySQL protocol
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.NetJava
Python
R
Scala
Java
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, Ryesnouser defined functions
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoDomain Eventsnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicehorizontal partitioning infoclient side managed; servers are not synchronizedyes, utilizing Spark Corehorizontal partitioning (by range and hash)
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 replicationnone
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
Immediate Consistency
Foreign keys infoReferential integritynodepending on modelnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoWrite ahead logyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlAzure Active Directory AuthenticationRole based authorizationnoRole based access control and fine grained access rights

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More resources
Microsoft Azure Data ExplorerOrigoDBSpark SQLStarRocks
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