Here’s the difference between Databricks and Metaphor. 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.
Metaphor is a search and discovery tool built for data scientists, data engineers, and AI practitioners. It aims to help all organizations better understand and manage their data through the power of the metadata knowledge graph.
Overview | ||
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Categories | Data Warehouses, Data Lakes | Data Discovery, Data Cataloging |
Stage | Late Stage | Early Stage |
Target Segment | Enterprise, Mid size | Mid size |
Deployment | SaaS | SaaS |
Business Model | Commercial | Commercial |
Pricing | Freemium, Contact Sales | Contact Sales, Free trial |
Location | San Francisco, US | US |
Companies using it | ||
Contact info |