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DBMS > Apache Kylin vs. MonetDB vs. Spark SQL vs. SQream DB

System Properties Comparison Apache Kylin vs. MonetDB vs. Spark SQL vs. SQream DB

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Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonMonetDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSQream DB  Xexclude from comparison
DescriptionA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackA relational database management system that stores data in columnsSpark SQL is a component on top of 'Spark Core' for structured data processinga GPU-based, columnar RDBMS for big data analytics workloads
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.25
Rank#170  Overall
#77  Relational DBMS
Score1.72
Rank#141  Overall
#64  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.74
Rank#224  Overall
#103  Relational DBMS
Websitekylin.apache.orgwww.monetdb.orgspark.apache.org/­sqlsqream.com
Technical documentationkylin.apache.org/­docswww.monetdb.org/­Documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.sqream.com
DeveloperApache Software Foundation, originally contributed from eBay IncMonetDB BVApache Software FoundationSQream Technologies
Initial release2015200420142017
Current release3.1.0, July 2020Dec2023 (11.49), December 20233.5.0 ( 2.13), September 20232022.1.6, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoMozilla Public License 2.0Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCScalaC++, CUDA, Haskell, Java, Scala
Server operating systemsLinuxFreeBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Linux
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes, ANSI Standard SQL 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.nono
Secondary indexesyesyesnono
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)yes infoSQL 2003 with some extensionsSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
JDBC
ODBC
.Net
JDBC
ODBC
Supported programming languagesC
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Java
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes, in SQL, C, Rnouser defined functions in Python
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding via remote tablesyes, utilizing Spark Corehorizontal and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoSource-replica replication available in experimental statusnonenone
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 integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
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 controlfine grained access rights according to SQL-standardno

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More resources
Apache KylinMonetDBSpark SQLSQream DB
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