Here’s the difference between Databricks and PostHog. 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.
Provider of product analytics tools. The features of the product include user behavior analysis, analyzation of trends, funnels, retention, and cohorts, compatibility, secure data access, etc. It also provides data retention, support, SSO/SAML, export to data lakes, pricing model, analytics stack, infrastructure, etc. The clients of the company include HASURA, TINKOFF, Staples, etc.
Overview | ||
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Categories | Data Warehouses, Data Lakes | Product Analytics |
Stage | Late Stage | Early Stage |
Target Segment | Enterprise, Mid size | Enterprise, Mid size |
Deployment | SaaS | Open source |
Business Model | Commercial | Open Source |
Pricing | Freemium, Contact Sales | Freemium, Contact Sales |
Location | San Francisco, US | San Francisco, California |
Companies using it | ||
Contact info |