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Discussion of sync engines typically goes hand in hand with local-first software. But it seems to be limited to use cases when the amount of data is on the smaller side. For example, can anyone imagine how there might be a local-first version of a recommendation algorithm (I'm thinking something TikTok-esque)? This would be a case where the determination of the recommendation relies on a large amount of data.

Or think about any kind of large-ish scale enterprise SaaS. One of the clients I'm working with currently sells a Transportation Management Software system (think logistics, truck loads, etc). There are very small portions of the app that I can imagine relying on a sync engine, but being able to search over hundreds of thousands of truck loads, their contents, drivers, etc seems like it would be infeasible to do via a sync engine.

I mention this because it seems that sync engines get a lot of hype and interest these days, but they apply to a relatively small subset of applications. Which may still be a lot, but it's a bit much to say they're the future (I'm inferring "of application development"--which is what I'm getting from this article).



I think that is where sync engines come in that allow doing arbitrary hybrid queries (across local and remote data) and then keeping the results of those hybrid queries in sync on the client.

This is one of the ideas that appears to be central to the genesis of Zero [1]

ElectricSQL allows for a similar pattern and PowerSync is also working on this [2]

[1] https://www.youtube.com/watch?v=rqOUgqsWvbw

[2] https://www.powersync.com/blog/powersync-2025-roadmap-sqlite...


Interesting! I'll give these a look.

Edit: I watched the presentation (which I really enjoyed) and also read the blog post. For anyone with less time, the answer is essentially: don't sync everything, treat the local data like a cache. Sync as much as you can into that cache, and then reach out to the server for other things.




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