Here’s the difference between Databricks and Databand. 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.
Databand is a provider of cloud and AI based data observability solutions. It provides an AI platform for unified data pipeline monitoring. It allows data scientists, data engineers, and data analysts to build, manage and optimize their processes for model training, experimentation, testing, and deployment. It is saturated with DataOps in providing automation and integration solutions through a pipeline framework for machine learning and iterative data products.
|Categories||Data Warehouses, Data Lakes||Data Quality Monitoring|
|Stage||Late Stage||Early Stage|
|Target Segment||Enterprise, Mid size||Mid size, Enterprise|
|Pricing||Freemium, Contact Sales||Contact Sales|
|Location||San Francisco, US||New York, US|
|Companies using it|