In this episode of The Data Engineering Show, the bros welcome the CEO DuckDB Labs and co-creator DuckDB, Hannes Mühleisen. They delve into the groundbreaking journey of DuckDB, an analytical database that processes billions of queries every month. Learn why DuckDB prioritizes broad compatibility over specialized optimizations, how its extension model works and the emerging solutions for database technology in the age of AI.
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Listen on Spotify or Apple Podcasts

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Episode Highlights

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The Purpose of DuckDB (01:04)

Hannes gives a full description of what DuckDB is as well as what it is designed to do. He describes the tool as one that understands SQL and is specifically designed to simplify complex analytical use cases.

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SQLite vs DuckDB (02:53)

Hannes compares two different tools stating that SQLite is an amazing system that is not meant for analytical queries but for transactional use cases while DuckDB is specifically designed for that exact purpose - analytical use cases. 

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The Importance of Collaboration (08:14)

Hannes states the need for community collaboration as the database engine space seems to have hundreds of brilliant people trying to solve the same problems. He shares his profound admiration for a team in Munich, praising them for their exploits in implementing concepts only described in paper.

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The Component-Based Architecture of DuckDB (11:25)

Hannes highlights a special feature in DuckDB, that is, it can be used as a component and he explains that the in-process architecture is a success because of the memory of data sharing that can be achieved.

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The Parquet Reader Journey (17:51)

Hannes explains how he built his Parquet Reader out of necessity, although he would have preferred not to. He shares how a creator named Ove Korn from Germany donated the reader to a project named “The Arrow Project” and managed it to the degree that the entire project depended on the use of the Parquet Reader and it became an issue to use both independently. Hannes adds that a parquet reader that is competent has no choice but to become a database engine which is one of the interesting things about development.

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The Role of AI in Database Interaction (22:41)

Hannes states that he doesn’t think that AI has a place in a database engine but rather, it is needed for optimization because the researchers who built their careers on optimization are out of jobs. He explains that the role of AI should be for assistance tasks and not for a total execution.

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SQL - A Defined Interface (29:20)

Hannes introduces us to a tool that allows us to pro-programmatically build a query called relational API stating that it helps to simplify the tasks of a programmer. Although, Hannes agrees that using a well-defined interface is important for components like databases, he also argues that SQL can provide a relatively defined behavior within a single system. 

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The Golden Age of Database (38:57)

Hannes concludes the episode by appreciating Firebolt and other engineers for taking on core engine tasks. He shares his excitement for the golden age of databases where there is a showcasing of what is possible.

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