webinar
High-Performance Full Text Search Directly on Iceberg via Lucene-Integrated Indexing
A technical discussion on how StarTree enables high-performance full-text search directly on Apache Iceberg – reducing scan-heavy queries without re-ingestion or data duplication.
Recorded on
June 17, 2026
While Data Lakehouses like Apache Iceberg provide massive, cost-effective scalability, they are fundamentally designed as scan-heavy engines. They lack the sub-second, “needle-in-a-haystack” full-text search and selective lookup capabilities provided by inverted indices found in traditional search engines.
This webinar explores how Apache Pinot fills this gap by integrating Apache Lucene segments directly into its distributed serving layer while maintaining the source of truth in Iceberg’s Parquet format.
- Segment-to-Parquet Virtualization: Pinot’s segment abstraction onto remote Iceberg/Parquet files without data duplication or heavy re-ingestion.
- Hybrid Index Pinning: The mechanics of pinning Lucene Inverted and Text Indexes to local NVMe storage on Pinot servers while leaving the raw data blobs on S3.
- Lucene I/O Orchestration: How Pinot optimizes query plans to minimize S3 “Time to First Byte” by leveraging metadata-heavy index structures.
