Here’s the difference between Datafold and Great Expectations. The comparison is based on pricing, deployment, business model, and other important factors.
Datafold offers a cloud-based quality assurance & monitoring solution for analytical data. The solution enables the users to automate the quality assurance of analytical data. It verifies the data to prevent data corruption every time a developer makes a change that impacts the data in production. It also provides integration over PostgreSQL, etc.
Great Expectations provides open-source enterprise data management solutions. It helps data teams eliminate pipeline debt, through data testing, documentation, and profiling. It maintains up-to-date data documentation by rendering expectations directly into clean, human-readable documentation. Users can join to GitHub and Slack community groups.
Overview | ||
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Categories | Data Quality Monitoring | Data Quality Monitoring |
Stage | Early Stage | Early Stage |
Target Segment | Enterprise, Mid size | Mid size |
Deployment | SaaS | On Prem |
Business Model | Commercial | Open Source |
Pricing | Freemium | Freemium |
Location | California, US | California, US |
Companies using it | ||
Contact info |