Apache Pinot

Clone this repo:
  1. dc17239 Package parquet and orc record reader into shaded jar (#4716) by Xiang Fu · 28 minutes ago master
  2. a78ac5c [TE][RCA] Fix the broken RCA algorithm tab (#4720) by Akshay Rai · 55 minutes ago
  3. 3579aae Remove the segment missing error message when acquiring segments (#4714) by Xiaotian (Jackie) Jiang · 29 hours ago
  4. 6ee6a41 [TE] Add unit test for DetectionEmailAlerter - fix casting bug (#4717) by Akshay Rai · 29 hours ago
  5. 5f01357 fix small typo in log message (#4707) by Bryan Ji · 3 days ago

Apache Pinot (incubating)

Build Status codecov.io Join the chat at https://gitter.im/linkedin/pinot license

Apache Pinot is a realtime distributed OLAP datastore, which is used to deliver scalable real time analytics with low latency. It can ingest data from offline data sources (such as Hadoop and flat files) as well as online sources (such as Kafka). Pinot is designed to scale horizontally.

These presentations on Pinot give an overview of Pinot:

Looking for the ThirdEye anomaly detection and root-cause analysis platform? Check out the Pinot/ThirdEye project

Key Features

  • A column-oriented database with various compression schemes such as Run Length, Fixed Bit Length
  • Pluggable indexing technologies - Sorted Index, Bitmap Index, Inverted Index, Star-Tree Index
  • Ability to optimize query/execution plan based on query and segment metadata
  • Near real time ingestion from Kafka and batch ingestion from Hadoop
  • SQL like language that supports selection, aggregation, filtering, group by, order by, distinct queries on fact data
  • Support for multivalued fields
  • Horizontally scalable and fault tolerant

Because of the design choices we made to achieve these goals, there are certain limitations present in Pinot:

  • Pinot is not a replacement for database i.e it cannot be used as source of truth store, cannot mutate data
  • Not a replacement for search engine i.e full text search, relevance not supported
  • Query cannot span across multiple tables

Pinot works very well for querying time series data with lots of Dimensions and Metrics. Example - Query (profile views, ad campaign performance, etc.) in an analytical fashion (who viewed this profile in the last weeks, how many ads were clicked per campaign).

Instructions to build Pinot

More detailed instructions can be found at Quick Demo section in the documentation.

# Clone a repo
$ git clone https://github.com/apache/incubator-pinot.git
$ cd incubator-pinot

# Build Pinot
$ mvn clean install -DskipTests -Pbin-dist

# Run Quck Demo
$ cd pinot-distribution/target/apache-pinot-incubating-<version>-SNAPSHOT-bin
$ bin/quick-start-offline.sh

Getting Involved


Check out Pinot documentation for a complete description of Pinot's features.


Apache Pinot is under Apache License, Version 2.0