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From Alan Ristić <>
Subject Blob vs. "normal" columns (internals) difference?
Date Wed, 03 Apr 2013 07:38:12 GMT
Hi guys,

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?

Tweet {
 id uuid,
 user blob


Tweet {
 id uuid,
 user_id uuid,
 user_name text,

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

*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 :)

Hvala in lp,
*Alan Ristić*

*w*: personal blog <>
 *t*: @alanristic <>
* l:* <>
*m*: ​068 15 73 88​

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