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Apache Pinot

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description Apache Pinot Overview

Apache Pinot is a real-time distributed OLAP datastore designed for ultra-low latency queries on large datasets. It was originally developed by LinkedIn to power their real-time analytics features. Pinot excels at 'user-facing' analytics, where sub-second response times are critical for the end-user experience (e.g., showing a user their recent activity or personalized recommendations). It supports multiple ingestion sources and provides high concurrency, making it perfect for applications that need to query streaming data with extreme speed.

help Apache Pinot FAQ

What is Apache Pinot designed for?

Apache Pinot is a real-time distributed OLAP (Online Analytical Processing) datastore designed to execute ultra-low latency queries on massive datasets. It is specifically optimized for "user-facing" analytics where sub-second response times are critical.

Which company originally created Apache Pinot?

The database was originally developed by LinkedIn to power their internal real-time analytics features, such as "Who Viewed My Profile." It was later open-sourced and became a top-level project at the Apache Software Foundation.

How does Apache Pinot achieve sub-second query latency?

Pinot achieves these ultra-fast query speeds by using a variety of indexing techniques, including inverted indices, star-tree indices, and range indices. It also pre-aggregates data and utilizes segment metadata to bypass irrelevant data during execution.

What is the difference between Apache Pinot and Apache Kafka?

Apache Kafka is a distributed event streaming platform used to ingest and move massive amounts of real-time data, whereas Pinot is the database where that data is permanently stored and queried. Often, data is streamed from Kafka directly into Pinot for real-time analytics.

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