Compare - Databricks VS Orchest

Here’s the difference between Databricks and Orchest. 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 Orchest

Orchest is an open-source, cloud-native, development environment built for data science. Orchest helps you build data pipelines, the easy way. No frameworks. No YAML. Just write Python and R code in notebooks.

Comparison Table

Overview
CategoriesData Warehouses, Data LakesWorkflow Orchestration
StageLate StageEarly Stage
Target SegmentEnterprise, Mid sizeMid Size, Enterprise
DeploymentSaaSOpen Source
Business ModelCommercialCommercial
PricingFreemium, Contact SalesFreemium / , Contact Sales
LocationSan Francisco, USRotterdam, Netherlands
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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