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DBMS > Microsoft Azure Data Explorer vs. OpenMLDB vs. Spark SQL vs. Trafodion

System Properties Comparison Microsoft Azure Data Explorer vs. OpenMLDB vs. Spark SQL vs. Trafodion

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Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonOpenMLDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionFully managed big data interactive analytics platformAn open-source machine learning database that provides a feature platform for training and inferenceSpark SQL is a component on top of 'Spark Core' for structured data processingTransactional SQL-on-Hadoop DBMS
Primary database modelRelational DBMS infocolumn orientedTime Series DBMSRelational 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
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.02
Rank#367  Overall
#37  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteazure.microsoft.com/­services/­data-exploreropenmldb.aispark.apache.org/­sqltrafodion.apache.org
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-exploreropenmldb.ai/­docs/­zh/­mainspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.html
DeveloperMicrosoft4 Paradigm Inc.Apache Software FoundationApache Software Foundation, originally developed by HP
Initial release2019202020142014
Current releasecloud service with continuous releases2024-2 February 20243.5.0 ( 2.13), September 20232.3.0, February 2019
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoApache 2.0Open Source infoApache 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++, Java, ScalaScalaC++, Java
Server operating systemshostedLinuxLinux
OS X
Windows
Linux
Data schemeFixed schema with schema-less datatypes (dynamic)Fixed schemayesyes
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-typesyesyesyes
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.yesnonono
Secondary indexesall fields are automatically indexedyesnoyes
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetyesSQL-like DML and DDL statementsyes
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
SQLAlchemy
JDBC
ODBC
ADO.NET
JDBC
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++
Go
Java
Python
Scala
Java
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, RnonoJava Stored Procedures
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynonono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicehorizontal partitioningyes, utilizing Spark CoreSharding
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 replicationnoneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
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 Authenticationfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
Microsoft Azure Data ExplorerOpenMLDBSpark SQLTrafodion
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