dlt

dlt (or Data Load Tool) is an open-source tool that enables data ingestion. As a Python library, DLT is composable and does not require a heavy architecture—just a simple pip install dlt is enough. To load data, you need to initialize the source, provide credentials, and configure the necessary endpoints. The code can then be executed directly within the orchestrator of your choice. DLT integrates seamlessly into both analytics and AI projects, supporting data ingestion for agents or more traditional models.

By default, dlt can load data into DuckDB, but it also works with all standard destinations. Its lightweight nature makes it a cost-effective tool for building EL processes in data lakes or data warehouses. Ingestion can be easily launched in Cloud Run containers or even within a CI/CD pipeline. With the standardization of Iceberg and DuckDB support, DLT also simplifies the transition between local work environments and production environments, streamlining what is often a complex process.

DLT also provides semantic contracts (data contracts) that overlay different sources, allowing for programmatic generation of everything downstream of ingestion.

MDN’S POINT OF VIEW

Data ingestion has always been a complex topic, whether using custom tools or off-the-shelf solutions. dlt brings structure to defining ingestions by combining the advantages of pre-built solutions while allowing for easy customization for specific use cases. Thanks to the dlt + DuckDB combination, it is now possible to set up ELT processes with very few lines of code.