Here’s the difference between Databricks and Preset. 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.
Preset provides data analytics platform for teams. It is an open-source platform that allows users to analyze and provides actionable insights about the data. Its products include Superset that enables visualize data and build dashboards to interpret and show hidden patterns from the data. It enables users to share reports and insights with teams and explore data analytics solutions. It can be integrated with Amazon RedShift, Google BigQuery, Presto and Druid.
Overview | ||
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Categories | Data Warehouses, Data Lakes | Business Intelligence (BI) |
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 |
Location | San Francisco, US | California, US |
Companies using it | ||
Contact info |