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DBMS > Apache Kylin vs. Hive vs. Microsoft Azure AI Search vs. Microsoft Azure Table Storage vs. Spark SQL

System Properties Comparison Apache Kylin vs. Hive vs. Microsoft Azure AI Search vs. Microsoft Azure Table Storage vs. Spark SQL

Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonHive  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonMicrosoft Azure Table Storage  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 stackdata warehouse software for querying and managing large distributed datasets, built on HadoopSearch-as-a-service for web and mobile app developmentA Wide Column Store for rapid development using massive semi-structured datasetsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSSearch engineWide column storeRelational DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.25
Rank#170  Overall
#77  Relational DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score5.52
Rank#59  Overall
#6  Search engines
Score4.04
Rank#77  Overall
#6  Wide column stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitekylin.apache.orghive.apache.orgazure.microsoft.com/­en-us/­services/­searchazure.microsoft.com/­en-us/­services/­storage/­tablesspark.apache.org/­sql
Technical documentationkylin.apache.org/­docscwiki.apache.org/­confluence/­display/­Hive/­Homelearn.microsoft.com/­en-us/­azure/­searchspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation, originally contributed from eBay IncApache Software Foundation infoinitially developed by FacebookMicrosoftMicrosoftApache Software Foundation
Initial release20152012201520122014
Current release3.1.0, July 20203.1.3, April 2022V13.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2commercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaScala
Server operating systemsLinuxAll OS with a Java VMhostedhostedLinux
OS X
Windows
Data schemeyesyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nononono
Secondary indexesyesyesyesnono
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)SQL-like DML and DDL statementsnonoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Thrift
RESTful HTTP APIRESTful HTTP APIJDBC
ODBC
Supported programming languagesC++
Java
PHP
Python
C#
Java
JavaScript
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceSharding infoImplicit feature of the cloud serviceyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infoImplicit feature of the cloud serviceyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic lockingno
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.nononono
User concepts infoAccess controlAccess rights for users, groups and rolesyes infousing Azure authenticationAccess rights based on private key authentication or shared access signaturesno

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More resources
Apache KylinHiveMicrosoft Azure AI SearchMicrosoft Azure Table StorageSpark SQL
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