In this episode of The Data Engineering Show, host Benjamin and co-host Eldad sit with CEO DuckDB Labs and co-creator DuckDB, Hannes Mühleisen.

• Talk about the journey of DuckDB, an open-source analytical database system designed as a universal wrangling tool.
• Explain how DuckDB differs from SQLite, highlighting the analytical and transactional use cases.
• Discuss DuckDB’s special feature and its approach to innovation including creating their Parquet Reader.
• Explore the simple and efficient ecosystem of DuckDB, allowing developers to add custom functionality without changing its core stability.
• Consider Hannes' perspective on the role of AI in databases.
• Delve into the system’s infrastructure, design choices and the dedication of the team to ensure a continuous, reliable database system.

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Hannes Mühleisen is the CEO of DuckDB Labs and a Professor in The Netherlands, renowned for co-creating DuckDB, an open-source analytical database system. With a background in database architecture and research from CWI database architectures group, he has pioneered the development of DuckDB as a universal data wrangling tool that can run everywhere from phones to space satellites. Under his leadership, DuckDB has achieved remarkable success, reaching 10 million downloads monthly and becoming a go-to solution for analytical database needs. His commitment to keeping DuckDB lightweight, portable, and hardware-agnostic while maintaining high performance has revolutionized how developers approach analytical database solutions. As both an academic and technology leader, Hannes brings unique insights into database architecture, open-source development, and the future of analytical data processing.

Episode Highlights:

• 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.

• 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. 

• 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.

• 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.

• 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.

• 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.

• 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. 

• The Golden Age of Database (38:57)

Quotes:

1. “DuckDB is a universal data wrangling tool. It is a relational data management system that speaks SQL designed to do well on analytical use cases.”

1. “We call ourselves the SQLite for analytics because it explains the original design goal of DuckDB very well.”

1. “Within the database engine space, we are all working to solve the same problems, and that's like, a hundred of us on the planet.”

1. “It actually turns out in order to make a competent parquet reader, you do need query execution. There is just no way around it.”

1. “I really like this golden age of databases we are in and personally, as somebody who really likes tables and SQL, I'm quite happy to see things like firebolt and others really working on core engine stuff.”

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