Here’s the difference between Databricks and Pace. 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.
Pace integrates natively with your business's most important data sources, unify and transform this disparate data into a standardized format that makes intuitive sense for B2B sellers, and that can be easily synced and used by CRMs. With Pace, you can see which insights drive positive sales behaviors and, by extension, the outcomes you care about. So, you can build a set of repeatable sales motions
Overview | ||
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Categories | Data Warehouses, Data Lakes | PLG CRM |
Stage | Late Stage | Early Stage |
Target Segment | Enterprise, Mid size | SMB's, Mid- size |
Deployment | SaaS | SaaS |
Business Model | Commercial | Commercial |
Pricing | Freemium, Contact Sales | Contact Sales |
Location | San Francisco, US | New York, NY |
Companies using it | ||
Contact info |