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
Because of the design choices we made to achieve these goals, there are certain limitations present in Pinot:
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).
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 the Quick Demo $ cd pinot-distribution/target/apache-pinot-incubating-<version>-SNAPSHOT-bin $ bin/quick-start-offline.sh
Please refer to Kubernetes Readme to deploy Pinot using [Helm](https://helm.sh/docs/using_helm/#installing-helm and load demo data set.
Pinot also provides k8s integration with interactive query engine Presto and data visualization tool Apache Superset.
Check out Pinot documentation for a complete description of Pinot's features.
Apache Pinot is under Apache License, Version 2.0