Pipeline Orchestration

What is Dagster, and How to Deploy It in an Enterprise Data Stack?

Last updated on
April 10, 2025
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What is Dagster?

Dagster is a Python-native data orchestrator for complex, modern data pipelines. It emphasizes local testability, a strong focus on asset-based dependencies, and an intuitive UI for monitoring. Unlike task-centric tools like Airflow, Dagster's core abstractions of 'ops', 'assets', and 'resources' facilitate code-native pipeline definitions that integrate better with your tech stack (e.g., dbt, ML libraries). This shift enables cleaner development, testability, and greater data platform reliability. While other tools force ETL to conform to workflow patterns, Dagster's model allows those data workflows to be developed organically from Python development habits.

Use cases for Dagster

Streamline Hospital Staffing with AI Demand Forecasting

Schedule Preventive Maintenance for Energy Infrastructure

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Why is Dagster better on Shakudo?

Why is Dagster better on Shakudo?

Core Shakudo Features

Own Your AI

Keep data sovereign, protect IP, and avoid vendor lock-in with infra-agnostic deployments.

Faster Time-to-Value

Pre-built templates and automated DevOps accelerate time-to-value.
integrate

Flexible with Experts

Operating system and dedicated support ensure seamless adoption of the latest and greatest tools.

See Shakudo in Action

Neal Gilmore
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