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Dagster Labs

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2 reviews
  • 2 profiles
  • 10 categories
Average star rating
4.5
Serving customers since
2018

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Dagster Labs Reviews

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AB
Aarsh B.
01/13/2026
Validated Reviewer
Review source: Thank You page

Dagster: Review

Dagster stands out for its asset‑centric approach to data orchestration, treating data as first‑class assets rather than just tasks. This makes pipelines more reliable, transparent, and easier to monitor. Users appreciate its strong integrations with modern data tools (like dbt, Snowflake, and Databricks), built‑in observability and monitoring, and a developer‑friendly design that emphasizes testability and maintainability. Its scalability across small and enterprise workflows ensures long‑term relevance, while the clear abstractions reduce complexity compared to older orchestrators.
Kelvin Ngoc Nguyen L.
KL
Kelvin Ngoc Nguyen L.
Building Multi-Agent Systems with LLMs @ Knoetic
06/19/2025
Validated Reviewer
Review source: G2 invite
Incentivized Review

Much more advanced and modern alternative to Apache Airflow

The tool is very sophisticated, modern and suitable for almost all use-cases of data engineering.

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HQ Location:
San Francisco ,California ,United States

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What is Dagster Labs?

Dagster Labs is the company behind Dagster, an open-source data orchestrator for machine learning, analytics, and ETL (Extract, Transform, Load) pipelines. Their platform is designed to improve productivity, reliability, and observability throughout the data lifecycle, catering especially to the needs of data engineers and data scientists. Dagster enables teams to define, structure, and manage workflows seamlessly, making data assets production-ready more efficiently.Rooted in a robust community and driven by the principles of collaborative development, Dagster emphasizes integration and compatibility with the existing modern data stack, including popular tools and platforms in the data ecosystem. Their website, https://www.dagster.io, serves as a hub for documentation, community interaction, and further insights into how Dagster can be utilized to build and scale complex data pipelines.\n

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Year Founded
2018