Have you run into issues with balancing schema flexibility and data consistency as your app grows? With Fauna’s adaptive schema enforcement, you can start with a schemaless collection, progressively add strict schema over time, and evolve it with zero-downtime migrations to meet growing data requirements. This means you gain all the benefits of strict data consistency when you need it—without compromising flexibility in the early stages of development. If you’re curious about how it works, check out our step-by-step tutorial on progressively defining and enforcing document types in Fauna. 👉 Dive into the tutorial here: https://lnkd.in/d78g4i6G #databaseschema #serverless
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I have a small project developing a simple app to analyze land cover change from 1985 to 2020. In the app, you can visualize land cover from 1985-2020 per 5 years and show the area change using the geospatial data you provided. You can also download the CSV of the land cover area change. Demo video: https://lnkd.in/e5ZN8QM5 Try the app yourself: https://lnkd.in/e7Kz892b Also, the GitHub if you want to try to develop one: https://lnkd.in/eTDaABwf This app is inspired by Samapriya Roy, Ph.D. post https://lnkd.in/epcmAXmf about the 1985 to 2020 Land Cover Change data GLC_FCS30D which is made by Liangyun Liu, Xiao Zhang, & Tingting Zhao. I developed the application using the NextJS framework, React, Maplibre, and Google Earth Engine. #webgis #remotesensing #lulc #landcover #landcoverchange #remotesensing #application #next #react #maplibre #googleearthengine
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