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DBMS > Apache Kylin vs. GBase vs. Spark SQL

System Properties Comparison Apache Kylin vs. GBase vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonGBase  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 stackAn analytical database for business intelligence with large customers in China.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.26
Rank#175  Overall
#81  Relational DBMS
Score1.05
Rank#193  Overall
#90  Relational DBMS
Score19.56
Rank#34  Overall
#21  Relational DBMS
Websitekylin.apache.orgwww.gbase.cnspark.apache.org/­sql
Technical documentationkylin.apache.org/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation, originally contributed from eBay IncApache Software Foundation
Initial release20152014
Current release3.1.0, July 2020GBase 8a3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScala
Server operating systemsLinuxLinux
OS X
Windows
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyes
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.nono
Secondary indexesyesno
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)SQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesJava
Python
R
Scala
Server-side scripts infoStored proceduresno
Triggersno
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlno

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More resources
Apache KylinGBaseSpark SQL
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