Cover Image for Webinar: Apache Iceberg + Polaris
Cover Image for Webinar: Apache Iceberg + Polaris
Avatar for OLake Community Events
We organise community events and webinars surrounding Data enginnering topics like CDC, Apache Iceberg, ETL from Database to Data Lakehouses
31 Went

Webinar: Apache Iceberg + Polaris

Virtual
Registration
Past Event
Welcome! To join the event, please register below.
About Event

Webinar Overview

This session explores the evolution of metadata catalogs in the lakehouse era, the challenges organizations face with traditional solutions, and why open catalog standards are critical for interoperability. The focus will be around Apache Polaris that's an Iceberg-native, open catalog designed to eliminate vendor lock-in, standardize metadata access so we will revolve our topics around the same here. Attendees will gain both foundational understanding and technical insights into Polaris's architecture, setup flow, and adoption journey.

Agenda

  1. Introduction to Data Catalogs in the Lakehouse Era

  2. Challenges with Traditional Metadata Catalogs

  3. The Case for Open Catalog Standards

  4. Apache Polaris: An Open, Iceberg-Native Catalog

    1. Why Polaris was created: filling the gap for a community-driven, Iceberg-first, open catalog

    2. Core principles: Vendor neutrality and open governance, Native support for Iceberg schema evolution and table versioning

    3. How Polaris differs from others: Engine-agnostic, unlike Unity Catalog or AWS Glue

    4. Architecture (surface-level): catalog service, metadata store, API layer, and engine connectors

  5. Quick setup and adoption journey: Running Polaris locally, Configuring with Iceberg, Connecting Dremio for first queries, Common pitfalls in setup/migration and how to avoid them

  6. Adoption perspective: incremental rollout (local → dev → production), lessons from early adopters, troubleshooting tips

Avatar for OLake Community Events
We organise community events and webinars surrounding Data enginnering topics like CDC, Apache Iceberg, ETL from Database to Data Lakehouses
31 Went