Overview
dltHub offers two core products: dlt , an open-source Python library for building data pipelines, and dltHub Pro , an agentic platform that deploys, monitors, and scales those pipelines. Developers describe their needs in natural language, and an AI agent scaffolds the entire pipeline—source, destination, schema, incremental loading, and tests—in pure Python. With a single command, dltHub Pro deploys pipelines to production with scheduling, alerting, and observability configured automatically. The platform is used by thousands of developers and supports over 9,700 data sources.
Application scenarios
CRM data integration
Build a pipeline that loads CRM contacts and deals into a warehouse using dlt.
REST API ingestion
Connect to any API and load data automatically via the REST API Pipeline workflow.
Prototyping and validation
Mid-level engineers can spin up a prototype, browse raw data in a local DuckDB workspace, and validate SQL schemas without senior oversight.
Production deployment
Deploy pipelines with one command, including automatic scheduling, alerting, and observability.
Data exploration
Browse loaded data, inspect schemas, and validate results in an interactive notebook.
Transformation workflows
Annotate sources, create ontologies, generate common data models, and create transformations.
Core features
Agentic workflows
Complete, guided sequences of skills, commands, rules, and MCP for every phase of data engineering—not just autocomplete or a chatbot.
Natural language prompting
Describe what you need in plain English, and the agent scaffolds the entire dlt pipeline.
One-command deployment
Deploy pipelines to production with scheduling, alerting, and observability configured automatically.
Agent-friendly documentation
Specialized docs designed for AI agents to read and act on.
Interactive notebook workspace
Browse loaded data, inspect schemas, and validate results directly in dltHub Pro.
Guardrails for agents
Maintained by dltHub, controlling the infrastructure agents and pipelines operate on.
9,700+ sources
Extensive library of pre-built source connectors for data movement.
Open-source core
dlt is a free, open-source Python library with no backend required.
Target users
Data engineers, mid-level engineers, and staff data engineers who need to build, prototype, and deploy data pipelines quickly. The platform is designed to unblock teams by letting less senior engineers spin up prototypes and validate schemas without senior oversight. It also serves AI agents directly, enabling agentic data workflows.
How to use
Install dlt: Run pip install dlt to get the open-source library. Describe your pipeline: Prompt the agent in natural language (e.g., "Build a pipeline that loads CRM contacts and deals into my warehouse using dlt"). Agent creates the pipeline: The agent scaffolds source, destination, schema, incremental loading, and tests in pure Python. Deploy with dltHub Pro: Run pip install dlt[hub] and use a single command to deploy to production with scheduling, alerting, and observability. Verify results: Browse loaded data, inspect schemas, and validate results in the interactive notebook workspace.
Effect review
The real-world feedback from Tasman Analytics highlights a key unlock: mid-level engineers can independently prototype, inspect raw data in DuckDB, and validate schemas without pulling in senior staff. This "prototype, inspect, fix, re-run" loop is described as the platform's true value. The agentic workflows go beyond simple autocomplete, providing guided sequences with guardrails that agents cannot skip. For teams building data pipelines at scale, dltHub delivers a practical, agent-first approach that reduces dependency on senior engineers while maintaining production-grade reliability.
Frequently asked questions
What is dlt?
dlt is an open-source Python library that simplifies building data pipelines by automatically inferring schemas and handling data loading.
What is dltHub Pro?
dltHub Pro is an agentic platform that extends dlt with deployment, monitoring, and scaling capabilities for production pipelines.
Is dlt free to use?
Yes, dlt is open-source and free. dltHub Pro offers additional paid features for enterprise use.
Who uses dlt?
dlt is used by thousands of developers to build and manage data pipelines efficiently.
What are the main benefits of dlt?
dlt reduces manual coding, handles schema evolution automatically, and supports various data destinations.
Launch URL
https://dlthub.com/Tags
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