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DBMS > MarkLogic vs. Microsoft Azure Data Explorer vs. Microsoft Azure Table Storage vs. Sadas Engine vs. Solr

System Properties Comparison MarkLogic vs. Microsoft Azure Data Explorer vs. Microsoft Azure Table Storage vs. Sadas Engine vs. Solr

Editorial information provided by DB-Engines
NameMarkLogic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSadas Engine  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionOperational and transactional Enterprise NoSQL databaseFully managed big data interactive analytics platformA Wide Column Store for rapid development using massive semi-structured datasetsSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS infocolumn orientedWide column storeRelational DBMSSearch engine
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
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Score0.07
Rank#373  Overall
#157  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websitewww.marklogic.comazure.microsoft.com/­services/­data-explorerazure.microsoft.com/­en-us/­services/­storage/­tableswww.sadasengine.comsolr.apache.org
Technical documentationdocs.marklogic.comdocs.microsoft.com/­en-us/­azure/­data-explorerwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationsolr.apache.org/­resources.html
DeveloperMarkLogic Corp.MicrosoftMicrosoftSADAS s.r.l.Apache Software Foundation
Initial release20012019201220062006
Current release11.0, December 2022cloud service with continuous releases8.09.6.1, May 2024
License infoCommercial or Open Sourcecommercial inforestricted free version is availablecommercialcommercialcommercial infofree trial version availableOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++Java
Server operating systemsLinux
OS X
Windows
hostedhostedAIX
Linux
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-free infoSchema can be enforcedFixed schema with schema-less datatypes (dynamic)schema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fields
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-typesyesyesyes infosupports customizable data types and automatic typing
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.yesyesnonoyes
Secondary indexesyesall fields are automatically indexednoyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyes infoSQL92Kusto Query Language (KQL), SQL subsetnoyesSolr Parallel SQL Interface
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
RESTful HTTP APIJDBC
ODBC
Proprietary protocol
Java API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
Groovy
Java
PHP
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyes infovia XQuery or JavaScriptYes, possible languages: KQL, Python, RnonoJava plugins
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynonoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceSharding infoImplicit feature of the cloud servicehorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneyes
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-sparknonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infocan act as a resource manager in an XA/JTA transactionnooptimistic lockingoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, with Range Indexesnonoyes infomanaged by 'Learn by Usage'yes
User concepts infoAccess controlRole-based access control at the document and subdocument levelsAzure Active Directory AuthenticationAccess rights based on private key authentication or shared access signaturesAccess rights for users, groups and roles according to SQL-standardyes

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More resources
MarkLogicMicrosoft Azure Data ExplorerMicrosoft Azure Table StorageSadas EngineSolr
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