Here’s the difference between Databricks and Flyte. 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.
Flyte provides a cloud-based machine learning and data processing platform. The open source structured programming and distributed solution enables concurrent, scalable and maintainable workflows for machine learning and data processing. Uses protocol buffers as the specification language to specify these workflows and tasks.
Overview | ||
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Categories | Data Warehouses, Data Lakes | Workflow Orchestration |
Stage | Late Stage | Early Stage |
Target Segment | Enterprise, Mid size | Mid size |
Deployment | SaaS | On Prem |
Business Model | Commercial | Open Source |
Pricing | Freemium, Contact Sales | Freemium |
Location | San Francisco, US | US |
Companies using it | ||
Contact info |