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DBMS > Apache Kylin vs. Microsoft Azure Data Explorer vs. Realm

System Properties Comparison Apache Kylin vs. Microsoft Azure Data Explorer vs. Realm

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Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRealm  Xexclude from comparison
DescriptionA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackFully managed big data interactive analytics platformA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data
Primary database modelRelational DBMSRelational DBMS infocolumn orientedDocument store
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
Score1.14
Rank#171  Overall
#78  Relational DBMS
Score3.57
Rank#81  Overall
#44  Relational DBMS
Score7.34
Rank#50  Overall
#8  Document stores
Websitekylin.apache.orgazure.microsoft.com/­services/­data-explorerrealm.io
Technical documentationkylin.apache.org/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerrealm.io/­docs
DeveloperApache Software Foundation, originally contributed from eBay IncMicrosoftRealm, acquired by MongoDB in May 2019
Initial release201520192014
Current release3.1.0, July 2020cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava
Server operating systemsLinuxhostedAndroid
Backend: server-less
iOS
Windows
Data schemeyesFixed 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.noyesno
Secondary indexesyesall fields are automatically indexedyes
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)Kusto Query Language (KQL), SQL subsetno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
Java infowith Android only
Objective-C
React Native
Swift
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, Rno inforuns within the applications so server-side scripts are unnecessary
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoChange Listeners
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyes
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.nonoyes infoIn-Memory realm
User concepts infoAccess controlAzure Active Directory Authenticationyes

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More resources
Apache KylinMicrosoft Azure Data ExplorerRealm
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