Compare - Databricks VS Continual

Here’s the difference between Databricks and Continual. The comparison is based on pricing, deployment, business model, and other important factors.

About Databricks

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.

About Continual

Continual is the missing AI layer for the modern data stack. Get continually improving predictions – from customer churn to inventory forecasts – directly in your data warehouse. No complex engineering required.

Comparision Table

Overview
CategoriesData Warehouses, Data LakesFeature Store
StageLate StageEarly Stage
Target SegmentEnterprise, Mid sizeMid size, Enterprise
DevelopmentSaaSSaaS
Business ModelCommercialCommercial
PricingFreemium, Contact SalesContact Sales
LocationSan Francisco, USSan Francisco, California
Companies using it
Uber logoJMAN Group logoQuintoAndar logoAXS logoLucid logoGousto logoPluralsight logo
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