Airbyte vs Dagster

Side-by-Side Comparison (2026)

Airbyte
51.9
Overall Score
41 quotes
Cloud ETL/ELT
Dagster
70.7
Overall Score
15 quotes
Orchestration

Overview

Airbyte and Dagster serve the data pipeline space with different approaches. Airbyte scores 51.9/100 while Dagster scores 70.7/100 based on practitioner feedback.

Dimension Scorecard

Dimension
Airbyte
Dagster
Total Cost of Ownership
63
50
Support Quality
48
100
Setup & Ease of Use
53
58

Airbyte Strengths

  • Open-source and community-driven approach
  • Extensive connector library and ability to build custom connectors
  • Lower pricing compared to proprietary solutions
  • Flexible deployment options (cloud and self-hosted)
  • Good for teams with custom integration needs

Dagster Strengths

  • Referenced strength from user feedback
  • Additional capability noted by users
  • Feature or approach valued by practitioners

When to Pick Each Vendor

Airbyte

Choose Airbyte for: Open-source and community-driven approach and Extensive connector library and ability to build custom connectors. It's particularly strong for teams needing cloud etl/elt.

Dagster

Choose Dagster for: Referenced strength from user feedback and Additional capability noted by users. It excels where orchestration is the priority.

Evidence from the Community

Airbyte Quotes

Very Negative hn
"Even a simple installation of airbyte on my local machine fails :( I tried docker-compose up!"
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Very Positive hn
"It is way easier for the community and for us to build connectors that meet quality standards"
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Very Negative hn
"Airbyte (457 RPS - 101x slower before it failed the long test)"
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Dagster Quotes

Very Positive hn
"I love the Dagit server and UI and that I can orchestrate pipelines over HTTP"
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Very Positive hn
"the team is extremely responsive on both Slack and GitHub"
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Negative hn
"I took a look at that for some machine learning things I was playing with but I found dvc"
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The Verdict

Both are production-ready options. Select based on your primary need: open-source and community-driven approach with Airbyte, or referenced strength from user feedback with Dagster.

Last updated: Jun 17, 2026