Dagster

Enterprise-grade data orchestrator for scalable, reliable data pipelines

Venture Funded$30M+Series BAndreessen HorowitzSequoia CapitalAmplify Partners

data orchestrationpipeline observabilityscalable workflowsmetadata management

About

Dagster enables enterprises to build, run, and observe data pipelines with strong governance and observability at scale. It supports compliance needs through robust metadata tracking and integrates seamlessly with modern data infrastructure. Designed for reliability and extensibility, Dagster empowers teams to manage complex workflows across hybrid environments.

This description came from a bulk import and has not yet been checked against the vendor's own page. Treat it as unverified.

Enterprise Readiness

from cataloged data

Not scored. Nobody has checked this entry against Dagster’s own site yet, so the signals below are unverified and we will not turn them into a rating. The breakdown shows what our record holds.

Security & ComplianceNot disclosed

No compliance certifications listed

Deployment FlexibilityStrong

Flexible deployment: Cloud, On-Premise, Hybrid, Self-Hosted

Integration DepthStrong

8 documented integrations

Proven AdoptionPartial

6 documented use cases

Company MaturityStrong

Founded 2018 · Series B

Composite of public compliance, deployment, integration, adoption, and company signals. “Not disclosed” reflects gaps in available data, not a vendor deficiency.

Independently sourced

Pulled directly from regulator filings and platform APIs. No vendor or editorial input.

Activity classifier

Active

last GitHub commit 0d ago

GitHub API2026-05-27

dagster-io

Open source product· 16.1k★· Apache-2.0· active 3mo ago

Python · Shell · Go · HTML

cooling · +195★ (+1.2%) 30d

PyPI registry

dagster

v1.13.6· released 3mo ago

OSV vulnerability feed2026-08-24

6 known advisories

1 high· 5 other· last update 2mo ago

Enterprise Use Cases

Enterprise data pipeline orchestration

Data quality monitoring and observability

Hybrid cloud data workflow management

Metadata-driven compliance auditing

Automated ETL/ELT workflows

Cross-team data collaboration

Integrations

SnowflakeDatabricksAWSGoogle Cloud PlatformKubernetesAirflowdbtSlack

How Dagster compares

Tool	Readiness	Pricing	Deployment	Compliance	Integrations
Dagster	Not scored	Freemium	Cloud, On-Premise, Hybrid, Self-Hosted	—	8
Airbyte	Not scored	Freemium	Cloud, On-Premise, Hybrid, Self-Hosted	—	8
Astronomer Astro	70 · Strong	Enterprise	Cloud, On-Premise, Hybrid, Self-Hosted	—	8
Elastic AI	70 · Strong	Enterprise	Cloud, On-Premise, Hybrid, Self-Hosted	—	8

Peers from the same category, ranked by Enterprise Readiness. Readiness is a composite of cataloged compliance, deployment, integration, adoption, and company signals.

Frequently Asked Questions

What is Dagster used for?

Dagster is enterprise-grade data orchestrator for scalable, reliable data pipelines. It is commonly used for enterprise data pipeline orchestration, data quality monitoring and observability, hybrid cloud data workflow management, and metadata-driven compliance auditing.

Is Dagster free, and how is it priced?

Dagster offers a free tier, with paid plans that add capacity and features.

How can Dagster be deployed?

Dagster supports Cloud, On-Premise, Hybrid, and Self-Hosted deployment. On-premise and self-hosted options support data-residency and air-gapped requirements.

What does Dagster integrate with?

Dagster documents 8 integrations, including Snowflake, Databricks, AWS, Google Cloud Platform, Kubernetes, and Airflow.

When was Dagster founded?

Dagster was founded in 2018 and has raised $30M+ in funding.

Is Dagster enterprise-ready?

Based on cataloged data, Dagster has an Enterprise Readiness score of 69/100 (Strong tier), derived from its compliance, deployment, integration, adoption, and company-maturity signals.

Quick Facts

PricingFreemium

DeploymentCloud, On-Premise, Hybrid, Self-Hosted

Founded2018

Funding$30M+

CategoryData & MLOps

Procurement

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