We use it a lot for a specific use-case and it works great. Mongo has come a long long way since the release over a decade ago, and if you keep it in Majority Read and Write, it's very reliable.
Also, on some things, it allows us to pivot much faster.
And now with the help of LLMs, writing "Aggregation Pipelines" are very fast.
I've been using Mongo while developing some analysis / retrieval systems around video, and this is the correct answer. Aggregation pipelines allow me to do really powerful search around amorphous / changing data. Adding a way to automatically update / recalculate embeddings to your database makes even more sense.
Do you have any tricks for writing and debugging pipelines? I feel like there are so many little hiccups that I spend ages figuring out if that one field name needs a $ or not.
Also, on some things, it allows us to pivot much faster. And now with the help of LLMs, writing "Aggregation Pipelines" are very fast.