Berlin-based dltHub has raised $8 million for its open source Python library that lets developers build data pipelines in minutes.
A quiet transformation in enterprise data engineering is being driven by dltHub, the Berlin-based company behind dlt, an open source Python library that automates complex data workflows. The company has secured $8 million in seed funding, led by Bessemer Venture Partners, after achieving 3 million monthly downloads and adoption across 5,000+ companies in regulated industries such as finance, healthcare and manufacturing.
The open-source dlt library enables developers to create production data pipelines in minutes — tasks once handled by specialised teams. By automating schema evolution, incremental loading and deployment, it brings data engineering within reach of any Python developer.
“Any Python developer should be able to bring their business users closer to fresh, reliable data,” said Matthaus Krzykowski, Co-founder and CEO of dltHub. “Our mission is to make data engineering as accessible, collaborative and frictionless as writing Python itself.”
Developers are increasingly pairing dlt with AI coding assistants to automate pipeline creation, accelerating productivity and reducing dependency on infrastructure specialists. The library’s LLM-optimised documentation makes it “extremely LLM friendly,” according to Hoyt Emerson, Data Consultant and Content Creator at The Full Data Stack.
Technically, dlt handles automatic schema evolution, supports incremental loading, and can deploy across any environment, from AWS Lambda to enterprise data stacks. It currently integrates with 4,600+ REST API sources and continues expanding through community-built connectors.
With its code-first, interoperable, and AI-native model, dltHub is reshaping how enterprises manage data. As Krzykowski noted, “LLMs aren’t replacing data engineers. But they radically expand their reach and productivity.”
