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Materialized views traditionally force a trade-off: data freshness vs. query performance.

What if you didn’t have to choose?
Join us for our January 2026 Virtual Meetup, where we’ll walk through an optimizer framework that reduces this trade-off by intelligently stitching together fresh partitions from storage with selectively recomputed stale partitions from base tables, delivering fast queries without sacrificing correctness.

What we’ll cover ?
- Core algorithm overview
- Snapshot-based staleness detection using Apache Iceberg
- Incremental refresh capabilities
- Performance considerations and known limitations
- Live demo

Who should attend ?
- Data Engineers and Data Analysts.
- Professionals working with materialized views, Apache Iceberg, or large-scale analytical platforms.

AI summary

By Meetup

Online meetup on Iceberg materialized views in Presto; for data engineers/analysts, learn an optimizer approach to balance freshness and performance with a live demo.

Related topics

Big Data
Data Analytics
Open Source
Software Engineering
Presto

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