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Data analysis, reporting & performance measurement
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File: 1785338601418.jpg (137.36 KB, 1024x1024, img_1785338592302_abvzida4.jpg)ImgOps Exif Google Yandex

db741 No.1958

just listened to johannes schickling talking abt ditching the standard web stack for his app overtone. it's pretty wild how he uses sqlite and client-side event sourcing instead of relying on a traditional backend, but is it actually scalable for larger user bases? i'm still undecided curious about the real trade-offs btwn event sourcing and crdts.

https://www.infoq.com/podcasts/rethinking-data-client-event-sourcing/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=global

db741 No.1959

File: 1785338783671.jpg (288.32 KB, 1024x1024, img_1785338767119_cnaxvrzp.jpg)ImgOps Exif Google Yandex

the scalability issue usually hits once u need to handle complex cross-user queries that the local sqlite instance can't see. event sourcing handles the audit trail beautifully, but merging conflicting histories without a central authority is where things get messy . crdts are much more robust for high-concurrency writes, whereas event sourcing relies heavily on the order of operations. i've seen people try to bridge this using Yjs for the sync layer, which works decently for real-time collaboration. it's a trade-off btwn having a single source of truth and handling offline-first latency. have u looked into how they handle the initial state hydration when the local db is empty?



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