Better than the other suggestions, but my experience is that you run into Cassandra's limitations really quick: you can't query on non-primary columns, and you can't join tables without pulling all the data down to the client and merge manually.
That's incorrect unless I'm misunderstanding what you mean with primary columns.. It's just not as efficient.
And missing joins are by design and one of the reasons cassandra is as fast as it is. And as I said before: it's not a drop in replacement. You need to architect your application around it's strength to leverage it's performance.
It is however usable as a rdbms replacement if you know what you're doing and your data is fine with eventual consistency.
And knowing what cassandra does with your data is important as well. It's actually a key-value store on steroids. Once you get that, it's limitations and strengths become obvious
> That's incorrect unless I'm misunderstanding what you mean with primary columns
I'm referring to "Cannot execute this query as it might involve data filtering and thus may have unpredictable performance. If you want to execute this query despite the performance unpredictability, use ALLOW FILTERING"
> It's just not as efficient.
That's what I thought, too, so I "allowed filtering". And crashed the database. (Apparently the correct solution here is to use Spark).
cassandra is at its heart a key-value store. for every queryable field, you need to create a new in-place copy of the data. so you're basically saving the data n-times, for each way you wish to query the data.
if you however try to query on a field which hasn't been marked as query-able, the cluster will have to basically select everything in the table and do a for loop to filter for the 'where' clause :-)
But i haven't used in production yet, so you've got more experience then i do
