dagster-dlt
Package for performing ETL/ELT tasks with dlt in Dagster.
Decision gist · record as of 2026-08-14
Yes. This is a lightweight, actively maintained integration with no security issues, permissive licensing, and low install friction. Install it if you are already using both Dagster and dlt and want to orchestrate dlt jobs as first-class Dagster assets rather than external processes.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later; both dagster and dlt must be installed and configured in your environment.
- Low friction install with two runtime dependencies (dagster and dlt).
- Package is actively maintained with a recent release and no known vulnerabilities.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial and private use with minimal restrictions; you may use, modify, and distribute the package freely provided you include the license notice.
last release 2026-08-14 (0 days) · last repo commit 2026-08-14 · 15,996 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 357,260 downloads/mo, #7,271 on PyPI
Alternatives
Verify before relying
pip install dagster-dlt
import dagster as dg
from dagster_dlt import DagsterDltResource
@dg.asset
def my_dlt_asset(dlt_resource: DagsterDltResource):
# Use dlt_resource to load data via dlt pipeline
pass- Specific dlt sources and destinations supported by this integration version
- Performance characteristics when orchestrating large-scale dlt pipelines
- Whether asset lineage and observability work across dlt and Dagster layers
What it is and what it does
dagster-dlt is a Dagster integration library that brings dlt's data loading capabilities into Dagster's asset-oriented orchestration model. It allows you to define dlt sources and destinations as Dagster assets, so they run within Dagster's scheduling, monitoring, and lineage tracking system. The package requires Python 3.10 or later and depends on both dagster and dlt as runtime libraries.
You use it when you want dlt's lightweight, source-to-destination data loading to be part of a larger Dagster data platform—where you need unified orchestration, observability, and asset management across your entire data stack. It sits between dlt's extraction-and-load simplicity and Dagster's declarative asset graph, letting you compose dlt jobs alongside other Dagster assets in a single Python codebase.
Use it for
- Build an ELT pipeline where dlt handles extraction and loading while Dagster orchestrates and monitors the full asset graph.
- Integrate dlt sources (e.g., Salesforce, Stripe) into a Dagster asset as part of a larger data warehouse workflow.
- Combine dlt's connector library with Dagster's testing and CI/CD tooling for reliable, repeatable data ingestion.
- Track data lineage and quality across dlt-loaded assets using Dagster's built-in observability and asset catalog.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
This is a lightweight, actively maintained integration with no security issues, permissive licensing, and low install friction. Install it if you are already using both Dagster and dlt and want to orchestrate dlt jobs as first-class Dagster assets rather than external processes.
Install
dagster-dlt on PyPI
Before you install
Low friction install with two runtime dependencies (dagster and dlt). Package is actively maintained with a recent release and no known vulnerabilities.
Requires Python 3.10 or later; both dagster and dlt must be installed and configured in your environment.
License in practice
Apache-2.0 permissive license allows commercial and private use with minimal restrictions; you may use, modify, and distribute the package freely provided you include the license notice.
Quickstart
pip install dagster-dlt
import dagster as dg
from dagster_dlt import DagsterDltResource
@dg.asset
def my_dlt_asset(dlt_resource: DagsterDltResource):
# Use dlt_resource to load data via dlt pipeline
passVerify before relying
- Specific dlt sources and destinations supported by this integration version
- Performance characteristics when orchestrating large-scale dlt pipelines
- Whether asset lineage and observability work across dlt and Dagster layers
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release <3.15,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesdagsterdlt |
| Maintenance | Actively maintained 0 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 357,260 / month, #7,271 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: dagster_dlt-0.29.18-py3-none-any.whl
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See also dagster-embedded-elt · dagster-sling · meltano · dagster-airbyte · dlthub · dlthub-client · dlt · dagster · dagster-graphql · dagster-aws