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DBMS > MarkLogic vs. Microsoft Azure Data Explorer vs. Spark SQL

System Properties Comparison MarkLogic vs. Microsoft Azure Data Explorer vs. Spark SQL

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Editorial information provided by DB-Engines
NameMarkLogic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionOperational and transactional Enterprise NoSQL databaseFully managed big data interactive analytics platformSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS infocolumn orientedRelational 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
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.marklogic.comazure.microsoft.com/­services/­data-explorerspark.apache.org/­sql
Technical documentationdocs.marklogic.comdocs.microsoft.com/­en-us/­azure/­data-explorerspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMarkLogic Corp.MicrosoftApache Software Foundation
Initial release200120192014
Current release11.0, December 2022cloud service with continuous releases3.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial inforestricted free version is availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Scala
Server operating systemsLinux
OS X
Windows
hostedLinux
OS X
Windows
Data schemeschema-free infoSchema can be enforcedFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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.yesyesno
Secondary indexesyesall fields are automatically indexedno
SQL infoSupport of SQLyes infoSQL92Kusto Query Language (KQL), SQL subsetSQL-like DML and DDL statements
APIs and other access methodsJava API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia XQuery or JavaScriptYes, possible languages: KQL, Python, Rno
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infocan act as a resource manager in an XA/JTA transactionnono
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.yes, with Range Indexesnono
User concepts infoAccess controlRole-based access control at the document and subdocument levelsAzure Active Directory Authenticationno

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More resources
MarkLogicMicrosoft Azure Data ExplorerSpark SQL
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