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Dagster

Data orchestration platform for building observable data pipelines

AI InfrastructureFounded 2018#16 of 55 in AI Infrastructure

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Company research

Current company data

No company research card is published for Dagster yet. The current company data below lists package, repository, and discussion metrics AI-Buzz can inspect today; AI-Buzz publishes a card when recent public metrics show a measured change with dated evidence and cited sources.

Package downloads (30d)

7.9M/30d

Dependent projects

336

dependents · latest

GitHub stars

15.8K

Hacker News

6/30d

Note: Public metrics are incomplete, and current data alone does not prove a trend; they do not show private usage, paid use, customer count, or product quality.

Company profile

What is Dagster?

Dagster provides a data orchestration platform that helps data teams define, develop, and operate robust, observable data pipelines. It focuses on developer productivity and data quality, making it easier to build and manage complex data workflows for machine learning and analytics. Its significance lies in streamlining the MLOps lifecycle by ensuring reliable data delivery and lineage.

Latest company data

Metric dates vary by source

Metric dates
PyPI downloads
PyPI dependents
GitHub stars
Hacker News mentions

Key metric

Package downloads (30d)

7.9M/30d

Tracked package: PyPI dagster

▲ +5%

Additional metrics

3 metrics

Metric

Dependent projects

336

Projects depending on tracked package: PyPI dagster

Metric

GitHub stars

15.8K

Main repository stars

Metric

Hacker News

6/30d

Position #27 in category discussion

Repository health

Maintenance data from the main open-source repository.

OpenSSF Scorecard
5.3
Key-person risk
1
External contributors
60
% of recent contributors outside the core team
Releases (30d)
0

Repository usage

Public repositories and source files importing packages tied to Dagster.

Repos importing
2860%

About Dagster

Dagster provides a data orchestration platform that helps data teams define, develop, and operate robust, observable data pipelines. It focuses on developer productivity and data quality, making it easier to build and manage complex data workflows for machine learning and analytics. Its significance lies in streamlining the MLOps lifecycle by ensuring reliable data delivery and lineage.

FoundersNick Schrock, Pete Hunt

Disclosed funding

Disclosed $50M · 3 rounds

Disclosed funding records total $50M. Category position #16 of 55 in AI Infrastructure.

Series B2023

Georgian

$33M
Series A2021

Sequoia Capital

$14M
Seed2019

Amplify Partners

$3M

Investors

Amplify PartnersGeorgianSequoia Capital

Tracked packages (1)

1 PyPI

dagster

PyPIMain PyPI package

dagster

Data orchestration platform for building observable data pipelines