dlt Hub

dlt (data load tool) is an open-source Python library designed for data platform teams to extract and load data efficiently. It simplifies the process of moving data from diverse and often messy sources, such as APIs, files, and databases, into structured, live datasets. Unlike other solutions, dlt operates purely as a Python library, eliminating the need for external backends or containers, and integrates seamlessly with existing Python environments like AI code editors or Jupyter Notebooks. It automates tedious data engineering tasks including schema inference, data normalization, and incremental loading, making it suitable for both micro and large infrastructures. dltHub is the broader vision extending beyond the core dlt library, aiming to transform complex data workflows into something accessible for any Python developer. It plans to encompass ELT, storage, and runtime capabilities, with a focus on governance, security, and compliance, particularly for highly regulated industries. The dltHub workflow also integrates with Large Language Models (LLMs) to assist developers in building and maintaining dlt pipelines and reports, accelerating the creation of data sources. The first release of dltHub for individual developers is anticipated in Q1 2026, with a goal to serve individual developers, small teams, and enterprises.