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DBMS > Apache Pinot vs. Databricks vs. PouchDB

System Properties Comparison Apache Pinot vs. Databricks vs. PouchDB

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonDatabricks  Xexclude from comparisonPouchDB  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyThe 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
Score0.38
Rank#275  Overall
#126  Relational DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Websitepinot.apache.orgwww.databricks.compouchdb.com
Technical documentationdocs.pinot.apache.orgdocs.databricks.compouchdb.com/­guides
DeveloperApache Software Foundation and contributorsDatabricksApache Software Foundation
Initial release201520132012
Current release1.0.0, September 20237.1.1, 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 systemsAll OS with a Java JDK11 or higherhostedserver-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.yesno
Secondary indexesyesyes infovia views
SQL infoSupport of SQLSQL-like query languagewith Databricks SQLno
APIs and other access methodsJDBCJDBC
ODBC
RESTful HTTP API
HTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languagesGo
Java
Python
Python
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 nodeshorizontal partitioningSharding 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 methodsyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 datayes
Durability infoSupport for making data persistentyesyes 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.noyes
User concepts infoAccess controlno
More information provided by the system vendor
Apache PinotDatabricksPouchDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache PinotDatabricksPouchDB
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