Compare - Databricks VS PipeRider

Here’s the difference between Databricks and PipeRider. 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 PipeRider

With PipeRider you can profile your data sources, create highly customizable data quality assertions, and generate insightful reports. It allows you to define the shape of your data once, and then use the data checking functionality to alert you to changes in your data quality.

Comparison Table

Overview
CategoriesData Warehouses, Data LakesData Quality Monitoring
StageLate StageEarly Stage
Target SegmentEnterprise, Mid sizeSMB's, Mid-Size
DeploymentSaaSOpen Source
Business ModelCommercialOpen Source
PricingFreemium, Contact SalesFreemium
LocationSan Francisco, USTaipei City, Taiwan
Companies using it
Uber logoJMAN Group logoQuintoAndar logoAXS logoLucid logoGousto logoPluralsight logoAstrato Analytics logoInfoPrice logosmartyutil logoCHONGTECHNOLOGIES logovmt pvt ltd logoCortex logo
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