Here’s the difference between Databricks and Stitch. 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.
Stitch provides extract, transform and Load (ETL) as a service for developers to securely manage the data preparation process. It allows users to configure their own data pipeline in a way that balances replication frequency and data selection by choosing the tables, fields, collections, and endpoints required in the warehouse. The product offers replicate API, monitoring & alerting during ETL process, security, compliance, cross-platform integration, and private infrastructure.
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 | Open Core |
Pricing | Freemium, Contact Sales | Contact Sales |
Location | San Francisco, US | Philadelphia Us |
Companies using it | ||
Contact info |