Here’s the difference between Databricks and Lightdash. 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.
Lightdash removes the gap between your data transformation layer and your data visualization layer. It enables data analysts and engineers to control all of their business intelligence (data transformations/business logic as well as data visualization) in a single place. Lightdash integrates with your dbt project and gives a framework for defining metrics and specifying joins between models all within your existing dbt YAML files. The data output from your dbt project is then available for exploring and sharing in Lightdash.
|Categories||Data Warehouses, Data Lakes||Metrics Store, Business Intelligence (BI)|
|Stage||Late Stage||Early Stage|
|Target Segment||Enterprise, Mid size||Mid size, SMBs|
|Business Model||Commercial||Open Source|
|Pricing||Freemium, Contact Sales||Freemium|
|Location||San Francisco, US||UK|
|Companies using it|