Here’s the difference between Databricks and Redpanda. 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.
Redpanda is the modern streaming data platform for developers. API-compatible with Apache Kafka, the product has a breakthrough architecture with 10x lower latencies, single binary deployment with built-in features, and tiered storage in the cloud with a unified streaming API. Redpanda offers a free community edition and commercial options for both self-hosted and SaaS.
Overview | ||
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Categories | Data Warehouses, Data Lakes | Data Streaming |
Stage | Late Stage | Mid Stage |
Target Segment | Enterprise, Mid size | Enterprise, Mid size |
Deployment | SaaS | SaaSOn Prem |
Business Model | Commercial | Commercial |
Pricing | Freemium, Contact Sales | Contact Sales |
Location | San Francisco, US | California, US |
Companies using it | ||
Contact info |