Here’s the difference between Databricks and Hevo Data. 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.
Hevo is a cloud based automated data pipeline preparation solution. It connects to the source and uses the transformation code to transfer data to the warehouse. Features include automatic detection and handling of the schema change, real-time alerts & notifications on the data pipeline, zero data loss, joining tables, and writing queries, integration with technology stacks, etc.
Overview | ||
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Categories | Data Warehouses, Data Lakes | ETL Tools |
Stage | Late Stage | Mid Stage |
Target Segment | Enterprise, Mid size | Enterprise, Mid size |
Deployment | SaaS | SaaS |
Business Model | Commercial | Commercial |
Pricing | Freemium, Contact Sales | Freemium |
Location | San Francisco, US | California, US |
Companies using it | ||
Contact info |