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DBMS > Apache Doris vs. Kyligence Enterprise vs. Microsoft Azure Data Explorer

System Properties Comparison Apache Doris vs. Kyligence Enterprise vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameApache Doris  Xexclude from comparisonKyligence Enterprise  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionAn MPP-based analytics DBMS embracing the MySQL protocolA distributed analytics engine for big data, built on top of Apache KylinFully managed big data interactive analytics platform
Primary database modelRelational DBMSRelational DBMSRelational DBMS infocolumn oriented
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
Score0.60
Rank#247  Overall
#113  Relational DBMS
Score0.46
Rank#266  Overall
#124  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitedoris.apache.org
github.com/­apache/­doris
kyligence.io/­kyligence-enterpriseazure.microsoft.com/­services/­data-explorer
Technical documentationgithub.com/­apache/­doris/­wikidocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software Foundation, originally contributed from BaiduKyligence, Inc.Microsoft
Initial release201720162019
Current release1.2.2, February 2023cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava
Server operating systemsLinuxLinuxhosted
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.nonoyes
Secondary indexesyesyesall fields are automatically indexed
SQL infoSupport of SQLyesANSI SQL for queries (using Apache Calcite)Kusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
MySQL client
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesJava.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresuser defined functionsYes, possible languages: KQL, Python, R
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano
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.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardAzure Active Directory Authentication

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More resources
Apache DorisKyligence EnterpriseMicrosoft Azure Data Explorer
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Apache Doris for Log and Time Series Data Analysis in NetEase: Why Not Elasticsearch and InfluxDB?
5 June 2024, hackernoon.com

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