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Pinot shares similar features with comparable OLAP datastores, such as [[Apache Druid]].<ref>{{cite book |last1=Ordonez |first1=Carlos |last2=Song |first2=Il-Yeol |last3=Anderst-Kotsis |first3=Gabriele |last4=Tjoa |first4=A. Min |last5=Khalil |first5=Ismail |title=Big Data Analytics and Knowledge Discovery: 21st International Conference, DaWaK 2019, Linz, Austria, August 26–29, 2019, Proceedings |date=2 October 2019 |publisher=Springer |isbn=978-3-030-27520-4 |page=170 |url=https://www.google.com/books/edition/Big_Data_Analytics_and_Knowledge_Discove/sf-pDwAAQBAJ?hl=en&gbpv=1&dq=Pinot+(data+store)+-wikipedia&pg=PA170&printsec=frontcover |language=en}}</ref><ref>{{cite book |last1=Uttamchandani |first1=Sandeep |title=The Self-Service Data Roadmap |date=10 September 2020 |publisher="O'Reilly Media, Inc." |isbn=978-1-4920-7520-2 |url=https://www.google.com/books/edition/The_Self_Service_Data_Roadmap/pEn8DwAAQBAJ?hl=en&gbpv=1&dq=Pinot+(data+store)+-wikipedia&pg=PT72&printsec=frontcover |language=en}}</ref> Like Druid, Pinot is a column-oriented database with various compression schemes such as [[Run-length encoding|Run Length]] and [[Variable-length encoding|Fixed Bit Length]]. Pinot supports pluggable [[Database index|indexing technologies]] - Sorted Index, [[Bitmap Index]], [[Inverted index|Inverted Index]], Star-Tree Index, and Range Index, which are what primarily differentiates Pinot from other OLAP datastores.
Pinot supports near real-time ingestion from streams such as [[Apache Kafka|Kafka]], [[AWS]] Kinesis and [[Batch processing|batch]] ingestion from sources such as [[Hadoop]], [[Amazon S3|S3]], [[Microsoft Azure|Azure]], [[Google Cloud Storage|GCS]]. Like
==See also==
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