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DBMS > Apache Kylin vs. Coveo vs. FatDB vs. Spark SQL

System Properties Comparison Apache Kylin vs. Coveo vs. FatDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonCoveo  Xexclude from comparisonFatDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentA .NET NoSQL DBMS that can integrate with and extend SQL Server.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSSearch engineDocument store
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.25
Rank#170  Overall
#77  Relational DBMS
Score2.11
Rank#118  Overall
#11  Search engines
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitekylin.apache.orgwww.coveo.comspark.apache.org/­sql
Technical documentationkylin.apache.org/­docsdocs.coveo.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation, originally contributed from eBay IncCoveoFatCloudApache Software Foundation
Initial release2015201220122014
Current release3.1.0, July 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC#Scala
Server operating systemsLinuxhostedWindowsLinux
OS X
Windows
Data schemeyeshybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes
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
Secondary indexesyesyesyesno
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)nono infoVia inetgration in SQL ServerSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP API.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
Supported programming languagesC#
Java
JavaScript
Python
C#Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infovia applicationsno
Triggersyesyes infovia applicationsno
Partitioning methods infoMethods for storing different data on different nodesyesShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlgranular access controls, API key management, content filtersno infoCan implement custom security layer via applicationsno

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Apache KylinCoveoFatDBSpark SQL
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