Here is example (fictional) model I have for learning purposes...
I'm currently storing the "User" object in a Tweet as blob value. So taking JSON of 'User' and storing it as blob. I'm wondering why is this better vs. just prefixing and flattening column names?
In one or other
1. Is size getting bigger in either one in storing one Tweet?
2. Has either choice have impact on read/write performance on large scale?
3. Anything else I should be considering here? Your view/thinking would be great.
Here is my understanding:
For 'ease' of update if for example user changes its name I'm aware I need to (re)write whole object in all Tweets in first "blob" example and only user_name column in second 'flattened' example. Which brings me that If I'd wanted to actually do this "updating/rewriting" for every Tweet I'd use second 'flattened' example since payload of only user_name is smaller than whole User blob for every Tweet right?
Nothing urgent, any input is valuable, tnx guys :)