Here’s the difference between Tera data and Databricks. The comparison is based on pricing, deployment, business model, and other important factors.
Teradata provides cloud data analysis and a customer data platform. It specializes in providing analytics data platforms, marketing, and analytic applications, and consulting services. It provides a database that delivers real-time results. It provides a data manager that unifies all the data about customers, suppliers, distributors, products, and locations to provide a single version of the master data. It also provides real-time integration and synchronization of a single view of master data.
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.
Overview | ||
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Categories | Data Warehouses | Data Warehouses, Data Lakes |
Stage | Late Stage | Late Stage |
Target Segment | Enterprise, Mid size | Enterprise, Mid size |
Deployment | SaaSOn Prem | SaaS |
Business Model | Commercial | Commercial |
Pricing | Free trial | Freemium, Contact Sales |
Location | California, US | San Francisco, US |
Companies using it | ||
Contact info |