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

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

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Editorial information provided by DB-Engines
NameBaseX  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOrigoDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionLight-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.Fully 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 processing
Primary database modelNative XML DBMSRelational DBMS infocolumn orientedDocument store
Object oriented DBMS
Relational 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
Score1.84
Rank#135  Overall
#4  Native XML DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.06
Rank#380  Overall
#50  Document stores
#19  Object oriented DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitebasex.orgazure.microsoft.com/­services/­data-explorerorigodb.comspark.apache.org/­sql
Technical documentationdocs.basex.orgdocs.microsoft.com/­en-us/­azure/­data-explorerorigodb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperBaseX GmbHMicrosoftRobert Friberg et alApache Software Foundation
Initial release200720192009 infounder the name LiveDB2014
Current release11.0, June 2024cloud service with continuous releases3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoBSD licensecommercialOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC#Scala
Server operating systemsLinux
OS X
Windows
hostedLinux
Windows
Linux
OS X
Windows
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)yesyes
Typing infopredefined data types such as float or dateno infoXQuery supports typesyes 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 collectionsyes
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 .NETno
Secondary indexesyesall fields are automatically indexedyesno
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetnoSQL-like DML and DDL statements
APIs and other access methodsJava API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
.NET Client API
HTTP API
LINQ
JDBC
ODBC
Supported programming languagesActionscript
C
C#
Haskell
Java
JavaScript infoNode.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.NetJava
Python
R
Scala
Server-side scripts infoStored proceduresyesYes, possible languages: KQL, Python, Ryesno
Triggersyes infovia eventsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoDomain Eventsno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud servicehorizontal partitioning infoclient side managed; servers are not synchronizedyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes 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 methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonodepending on modelno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datamultiple readers, single writernoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes 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 controlUsers with fine-grained authorization concept on 4 levelsAzure Active Directory AuthenticationRole based authorizationno

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BaseXMicrosoft Azure Data ExplorerOrigoDBSpark SQL
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