dlt Hub
dlt (data load tool) is an open-source Python library designed for data platform teams to extract and load data efficiently.
Our verdict
Who it's for
Lightweight Python code to move data from various sources into well-structured, live datasets.
Who should look elsewhere
dltHub (the extended platform) is still under development with a Q1 2026 release for individual developers
Pros
- +Open-source and production-ready
- +Python-native, no external backends or containers required
- +Automates complex data engineering tasks
- +Highly customizable with verified and custom sources
- +Supports LLM-assisted pipeline creation
Cons
- −dltHub (the extended platform) is still under development with a Q1 2026 release for individual developers
- −May require Python knowledge for advanced customization
Key features
- ✓Loads data from APIs, files, and databases
- ✓Schema inference and evolution
- ✓Data normalization
- ✓Incremental loading
- ✓Deduplication and SCD2 materializations
- ✓60+ pre-built verified data sources (e.g., SQL databases, Google Sheets, Salesforce)
- ✓Numerous destinations (e.g., Snowflake, Databricks, local databases, data lakes)
- ✓Custom source building with REST API toolkit or from scratch in Python
Pricing
| Plan | Price | Billing | Notes |
|---|---|---|---|
| Open Source | — | month | Loads data from various data sources into well-structured, live datasets; No need for backends or containers; Integrates with AI code editors and Jupyter Notebook |