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DBMS > Apache Kylin vs. Microsoft Azure AI Search vs. OrigoDB vs. Spark SQL

System Properties Comparison Apache Kylin vs. Microsoft Azure AI Search vs. OrigoDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonOrigoDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackSearch-as-a-service for web and mobile app developmentA fully ACID in-memory object graph databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSSearch engineDocument store
Object oriented DBMS
Relational DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#172  Overall
#79  Relational DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitekylin.apache.orgazure.microsoft.com/­en-us/­services/­searchorigodb.comspark.apache.org/­sql
Technical documentationkylin.apache.org/­docslearn.microsoft.com/­en-us/­azure/­searchorigodb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation, originally contributed from eBay IncMicrosoftRobert Friberg et alApache Software Foundation
Initial release201520152009 infounder the name LiveDB2014
Current release3.1.0, July 2020V13.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC#Scala
Server operating systemsLinuxhostedLinux
Windows
Linux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesUser defined using .NET types and collectionsyes
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.nonono infocan be achieved using .NETno
Secondary indexesyesyesyesno
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)nonoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP API.NET Client API
HTTP API
LINQ
JDBC
ODBC
Supported programming languagesC#
Java
JavaScript
Python
.NetJava
Python
R
Scala
Server-side scripts infoStored proceduresnoyesno
Triggersnoyes infoDomain Eventsno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicehorizontal partitioning infoclient side managed; servers are not synchronizedyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynodepending on modelno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlyes infousing Azure authenticationRole based authorizationno

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More resources
Apache KylinMicrosoft Azure AI SearchOrigoDBSpark SQL
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