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Databricks vs Maze: What are the differences?
What is Databricks? A unified analytics platform, powered by Apache Spark. Databricks Unified Analytics Platform, from the original creators of Apache Spark™, unifies data science and engineering across the Machine Learning lifecycle from data preparation to experimentation and deployment of ML applications.
What is Maze? Beautiful & actionable analytics for InVision prototypes. Create missions testers will perform on your InVision’s prototype and discover how your product’s design can be improved, with 0 lines of code.
Databricks and Maze belong to "General Analytics" category of the tech stack.
Some of the features offered by Databricks are:
- Built on Apache Spark and optimized for performance
- Reliable and Performant Data Lakes
- Interactive Data Science and Collaboration
On the other hand, Maze provides the following key features:
- InVision Analytics
- Prototype testing
- Clicks Heatmap
i-surance, Specify, and Fuchsia are some of the popular companies that use Maze, whereas Databricks is used by Auto Trader, Snowplow Analytics, and Fairygodboss. Maze has a broader approval, being mentioned in 3 company stacks & 8 developers stacks; compared to Databricks, which is listed in 7 company stacks and 4 developer stacks.
Pros of Databricks
- Best Performances on large datasets1
- True lakehouse architecture1
- Scalability1
- Databricks doesn't get access to your data1
- Usage Based Billing1
- Security1
- Data stays in your cloud account1
- Multicloud1
Pros of Maze
- Makes validating protos easier3
- Easy export and setup2