Revolutionizing Data Architecture: Hannes Mühleisen’s Insights at PyData Amsterdam 2025 🚀

www.pydata.org

Every data architecture diagram out there makes it abundantly clear who's in charge: At the bottom sits the analyst, above that is an API server, and on the very top sits the mighty data warehouse. This pattern is so ingrained we never ever question its necessity, despite its various issues like slow data response time, multi-level scaling issues, and massive cost.

But there is another way: Disconnect of storage and compute enables localization of query processing closer to people, leading to much snappier responses, natural scaling with client-side query processing, and much reduced cost.

In this talk, it will be discussed how modern data engineering paradigms like decomposition of storage, single-node query processing, and lakehouse formats enable a radical departure from the tired three-tier architecture. By inverting the architecture we can put user's needs first. We can rely on commoditised components like object store to enable fast, scalable, and cost-effective solutions.

PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.

PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.

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