Python for the Modern Data Lakehouse: PyStarburst, Ibis, and Beyond
Python has become the universal language of data, but connecting it efficiently to enterprise-scale compute remains a challenge. Many teams rely on heavy Spark clusters or brittle ad-hoc scripts to bridge batch and real-time workloads, creating governance gaps and performance tradeoffs.
In this 60-minute technical session, you’ll see how Starburst brings Python closer to your data. We’ll walk through Python integration across Galaxy and Starburst Enterprise, including:
- PyStarburst and Ibis DataFrame APIs: Express transformations in Python that compile to SQL and run on Starburst compute.
- Trino Python client: A lightweight option for executing SQL from Python.
- Python UDFs (Public Preview): Extend Starburst Enterprise with custom logic, including sandboxing and runtime constraints.
You’ll learn how each approach differs, and when to use which, for optimal performance, governance, and portability.
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Python has become the universal language of data, but connecting it efficiently to enterprise-scale compute remains a challenge. Many teams rely on heavy Spark clusters or brittle ad-hoc scripts to bridge batch and real-time workloads, creating governance gaps and performance tradeoffs.
In this 60-minute technical session, you’ll see how Starburst brings Python closer to your data. We’ll walk through Python integration across Galaxy and Starburst Enterprise, including:
- PyStarburst and Ibis DataFrame APIs: Express transformations in Python that compile to SQL and run on Starburst compute.
- Trino Python client: A lightweight option for executing SQL from Python.
- Python UDFs (Public Preview): Extend Starburst Enterprise with custom logic, including sandboxing and runtime constraints.
You’ll learn how each approach differs, and when to use which, for optimal performance, governance, and portability.
