Gnarly Data Waves

Episode 56

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September 10, 2024

What’s New in Dremio: Improved Automation, Performance + Catalog for Iceberg Lakehouses

Discover the new Dremio capabilities designed to make your Apache Iceberg data lakehouse the most efficient, scalable, and manageable platform for analytics and AI.  We’ll cover enhancements in performance, data ingestion, data processing, and federated query capabilities, aimed at helping you achieve the fastest, most scalable, and easiest to use lakehouse for all of your data.

Dremio unveiled new features in our latest release that enhance the creation, performance, and management of Apache Iceberg data lakehouses.

You will learn how Dremio delivers market-leading SQL query and write performance, improved federated query security and management as well as streamlined data ingestion by delivering:

– Live Reflections on Iceberg tables that will accelerate performance, ensure up-to-date data and reduce management overhead.

– Result Set Caching that can accelerate query performance up to 28X – Merge-on-Read that can enhance write and ingestion speed

– Auto Ingest Pipes that eliminate complex pipeline setup and maintenance

– User Impersonation for federated queries that allows for granular permissions, better access control, and user workload tracking

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What is Apache Polaris?

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What is Apache Polaris

Apache Polaris is an open-source catalog service purpose-built for managing Apache Iceberg tables in a distributed, multi-engine environment. At its core, Polaris implements the Iceberg REST Catalog API, providing a standardized, cloud-native method for connecting query engines with Iceberg metadata, without requiring tight coupling to storage systems.

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Delivering Data Products with a Lakehouse Architecture: Insights from BARC & Dremio

Learn how the data lakehouse powers scalable, reusable data products. Join BARC and Dremio for strategies and best practices.

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