Leveraging DuckDB and Delta Lake Together

@mehdio will have the pleasure of hosting Holly Smith from @Databricks to chat about all things related to Delta Lake and how its integration with DuckDB works! Get ready to quack and query table formats 👩‍💻

Resources :
DuckDB - Delta lake documentation : https://duckdb.org/docs/extensions/de...

#duckdb #deltalake #dataengineering

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Explore the powerful integration of the Delta Lake table format with DuckDB in this comprehensive technical deep dive. Joined by Holly Smith, Developer Advocate at Databricks, we uncover why standard Parquet files often fall short for modern data analytics and data engineering workflows. We discuss critical challenges such as schema enforcement, data quality control, and the complexities of handling updates and deletes in a data lake, setting the stage for how the Delta Lake open-source project provides a robust solution for your cloud data warehouse.

Discover the core architecture of Delta Lake, which enhances Parquet files with a transactional metadata layer known as the `_delta_log`. This key innovation brings database-level features like ACID transactions directly to object storage like S3, ensuring data reliability and consistency. We'll break down how this works under the hood, including how the Delta Log tracks file versions and handles operations like deletes efficiently using deletion vectors. This session explains why it's crucial for data engineers to interact with the Delta table abstraction rather than the raw Parquet files.

Get hands-on with practical examples showing how to query Delta Lake tables using DuckDB. We demonstrate the `delta_scan` command for reading data from both local files and large datasets on S3, showcasing the impressive speed DuckDB offers for local development and interactive analysis. We'll also touch on the new Delta Kernel, which aims to standardize and accelerate integrations across the data ecosystem. Learn how to leverage these tools in your workflow and see how MotherDuck can further optimize queries on your cloud data.

Finally, we look ahead at the evolving landscape of data table formats. This discussion covers the convergence of major players like Delta Lake, Apache Iceberg, and Hudi, and what it means for the future of the data warehouse. Gain valuable insights to inform your data architecture decisions, whether you're a data analyst or engineer building a scalable and efficient data platform with modern developer tools.