Here’s the difference between Databricks and Dagster. The comparison is based on pricing, deployment, business model, and other important factors.
Databricks provides a data lakehouse that unifies your data warehousing and AI use cases on a single platform. With Databricks, you can implement a common approach to data governance across all data types and assets, and execute all of your workloads across data engineering, data warehousing, data streaming, data science, and machine learning on a single copy of the data. Built on open source and open standards, with hundreds of active partnerships, Databricks easily integrates with your modern data stack. Additionally, Databricks uses an open standards approach to data sharing to eliminate ecosystem restrictions. Finally, Databricks provides a consistent data platform across clouds to reduce the friction of multicloud environments. Today, Databricks has over 7000 customers, including Amgen, Walmart, Disney, HSBC, Shell, Grab, and Instacart.
Dagster is an orchestrator that's designed for developing and maintaining data assets, such as tables, data sets, machine learning models, and reports.You declare functions that you want to run and the data assets that those functions produce or update. Dagster then helps you run your functions at the right time and keep your assets up-to-date.
Overview | ||
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Categories | Data Warehouses, Data Lakes | Workflow Orchestration |
Stage | Late Stage | Early Stage |
Target Segment | Enterprise, Mid size | Mid size, Enterprise |
Deployment | SaaS | On PremSaaS |
Business Model | Commercial | Open Source |
Pricing | Freemium, Contact Sales | Freemium, Contact Sales |
Location | San Francisco, US | United States |
Companies using it | ||
Contact info |