about us

The number of Python users increases by millions every year. The vast majority of these people use Python as a tool to solve problems at work. Our mission is to make Python practitioners autonomous when they create and use datasets in their organizations.

For this end, we are building data load tool (dlt), an open source Python library, for them. They use dlt in their Python scripts to turn messy, unstructured data into regularly updated datasets. It enables them to create highly scalable, easy-to-maintain, straightforward-to-deploy data pipelines without waiting for a data engineer's help. dlt is designed for a new wave of data practitioners that need to load the data in unexpected places and interact with the data infrastructure of a modern organization.

dltHub is inspired by the open-source movement that drove the machine learning revolution. Similar to how Python's open-source tools drive the current machine learning revolution, with dlt, we aim to extend the underlying open source principles to enterprise data and apply similar principles to it. Companies that adopt Python-friendly workflows will see revenue and productivity gains similar to those we have seen in AI in recent years.

We are dedicated to keeping dlt an open source project surrounded by a vibrant, engaged community. To make this sustainable, dltHub stewards dlt while also offering additional software and services that generate revenue (e.g., like GitHub does with Git).

Based in Berlin and New York City, dltHub was founded by experienced machine learning and data professionals and is supported by Dig Ventures and renowned technical founders from companies like Hugging Face, Rasa, Instana, Miro, and Matillion.