11 ms·
> Compressed column-stores hurt OLAP, because update throughput (the “on-line” in OLAP) is relatively bad. Uncompressed / array stores are quite good. But why
by davedx 7y ago
> Compressed column-stores hurt OLAP, because update throughput (the “on-line” in OLAP) is relatively bad. Uncompressed / array stores are quite good.
But why do you want high update throughout when you're doing mostly reads? Every definition I read about OLAP says this is one of the fundamental differences, or am I misunderstanding something?
- alexhutcheson 7y agoYour users want their dashboards and reports to contain data that's as up-to-date as possible. No one is happy about waiting 24 hours or more for a batch update to run if there are decisions they need to make right now. The difference vs. OLTP is that it might be acceptable for events to take minutes or even hours to be reflected in the database, vs. ~seconds or less for a transaction where the user is interacting and waiting for a confirmation.
- amylene 7y agoMost of the users I work with, when asked why they want more than daily batches, respond with something emotional and not business value. I had a request for real-time updates for a massive metric that is based around monthly usage. Ya just gotta push back, and hep people understand what the trade offs are for real-time. Most people don’t need it.
- quantified 7y agoAbsolutely true. The ones that do, do. For example, multiuser planning systems absolutely do. And those were what OLAP was originally intended to support.
- quantified 7y agoYou’re missing the important definitions from back when OLAP originated. There is a high update rate for the use cases I build software for.