Apache Pinot

Apache Pinot is an open‑source distributed OLAP database designed for real‑time analytics on large, streaming datasets. It stores data in a columnar format and supports fast ingestion, upserts, and a variety of join types, enabling sub‑second query latencies even at petabyte scale. The system provides a SQL query interface, rich indexing options, and built‑in multitenancy for isolated workloads.

The platform targets developers building user‑facing applications such as interactive dashboards, metrics APIs, and embedded analytics that must serve millions of concurrent users with low latency. It also serves AI agents and LLM‑powered systems that require fresh data for retrieval‑augmented generation, decision engines, and autonomous observability. High concurrency and real‑time streaming ingestion make it suitable for use cases like leaderboards, usage meters, and fraud detection.

Apache Pinot’s architecture emphasizes performance and scalability, offering high throughput, low query latency, and the ability to run locally for quick evaluation. It is used by engineering teams at several leading companies and is positioned as a stable, production‑ready solution for both human‑directed and agent‑directed analytics.