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DBMS > Apache Kylin vs. Databricks vs. PouchDB

System Properties Comparison Apache Kylin vs. Databricks vs. PouchDB

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Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonDatabricks  Xexclude from comparisonPouchDB  Xexclude from comparison
DescriptionA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.JavaScript DBMS with an API inspired by CouchDB
Primary database modelRelational DBMSDocument store
Relational DBMS
Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.25
Rank#170  Overall
#77  Relational DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Websitekylin.apache.orgwww.databricks.compouchdb.com
Technical documentationkylin.apache.org/­docsdocs.databricks.compouchdb.com/­guides
DeveloperApache Software Foundation, originally contributed from eBay IncDatabricksApache Software Foundation
Initial release201520132012
Current release3.1.0, July 20207.1.1, June 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaScript
Server operating systemsLinuxhostedserver-less, requires a JavaScript environment (browser, Node.js)
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or dateyesno
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.noyesno
Secondary indexesyesyesyes infovia views
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)with Databricks SQLno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
HTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languagesPython
R
Scala
JavaScript
Server-side scripts infoStored proceduresuser defined functions and aggregatesView functions in JavaScript
Triggersyes
Partitioning methods infoMethods for storing different data on different nodesSharding infowith a proxy-based framework, named couchdb-lounge
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backend
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlno
More information provided by the system vendor
Apache KylinDatabricksPouchDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache KylinDatabricksPouchDB
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