Here’s the difference between Databricks and Dremio. 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.
Dremio is a provider of analytical processing data lake engines. The features of the product include data security and control, SSO authentication, automatic backups, predictive pipelining, inbound impersonation, workload management, etc. The clients of the company include Henkel, Honeywell, NCR, UBS, Verisk, DIAGEO, etc.
Overview | ||
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Categories | Data Warehouses, Data Lakes | Data Warehouses, Data Lakes |
Stage | Late Stage | Mid Stage |
Target Segment | Enterprise, Mid size | Enterprise, Mid size |
Deployment | SaaS | SaaSOn Prem |
Business Model | Commercial | Commercial |
Pricing | Freemium, Contact Sales | Free trial |
Location | San Francisco, US | California, US |
Companies using it | ||
Contact info |