# How Apache Iceberg and Python Support Open, Incremental Data Lake Adoption

DevFeed: [How Apache Iceberg and Python Support Open, Incremental Data Lake Adoption](<https://devfeed.tech/articles/why-iceberg-python-is-the-future-of-open-data-lakes-80336.md>)

Original publisher: [Read original article](<https://dlthub.com/blog/iceberg-open-data-lakes>)

Author: Adrian Brudaru

Published: 2025-03-18T00:00:00Z

Content type: article

Language: en

Sources: [DLT Hub](<https://devfeed.tech/sources/dlt-hub.md>)

Topics: [Apache Iceberg](<https://devfeed.tech/topics/apache-iceberg.md>), [DLT](<https://devfeed.tech/topics/data-load-tool.md>), [AI Infrastructure](<https://devfeed.tech/topics/ai-infrastructure.md>), [Test-driven development](<https://devfeed.tech/topics/tdd.md>)

Tags: [ai-systems](<https://devfeed.tech/tags/ai-systems.md>), [apache-iceberg](<https://devfeed.tech/tags/apache-iceberg.md>), [community](<https://devfeed.tech/tags/community.md>), [compute-costs](<https://devfeed.tech/tags/compute-costs.md>), [data-engineering](<https://devfeed.tech/tags/data-engineering.md>), [data-lakes](<https://devfeed.tech/tags/data-lakes.md>), [python](<https://devfeed.tech/tags/python.md>)

## AI overview

The article argues that Apache Iceberg can make data lakes more interoperable through ACID transactions, schema evolution, and support across query engines. It describes how teams can adopt Iceberg incrementally with Python and dlt, and presents decoupled compute and storage as a way to control costs for analytics and AI workloads.

## Source excerpt

Data lakes are broken. Python + Iceberg fixes them. No lock-in. No silos. Just open, AI-ready data. Read on why and how to switch ->