Here’s the difference between Databricks and Amundsen. 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.
Open-source data discovery and metadata platform. Data engineers and analysts can search for data within the organization by a simple text search and the page rank search algorithm recommends results based on names, descriptions, tags, and querying/viewing activity on the table/dashboard. Also, it allows to build trust in data using automated metadata.
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 | On Prem |
Business Model | Commercial | Open Source |
Pricing | Freemium, Contact Sales | Free trial |
Location | San Francisco, US | US |
Companies using it | ||
Contact info |