5 ms·

Still don't understand why businesses buy this instead of scaling-out. Cost? Complexity?

SDGT 12y ago
The third and most important reason: They have someone to blame when shit goes tits up. Response time may still be abysmal, but "dammit we payed a million dollars for this!"
- th3iedkid 12y ago
  and one more thing with large volume transaction processing is scaling out on I/O and ETL jobs.Oracle (and other DB vendors) offer a lot of utilities that scale out perfectly with least of development time. For e.g. it would rather be a difficult deal to work with parsers to parse a Gigabit-data file with code we have to own up , than to use features these DBs directly offer to parallel-load into a ready to use table within minutes.
elliptic 12y ago
I'm not saying that Oracle hardware or software is the solution, but "scaling-out" is incredibly difficult in transaction processing. I worked at a mid-size tech company with what I imagine was a fairly typical workload, and we spent a ton of money on database hardware because it would have been either incredibly complicated or slow to maintain data integrity across multiple machines. I imagine that situation is fairly common.
AlisdairO 12y ago
Both, I suspect. When you consider the cost of engineer time needed to create high performance scale-out systems in a problem domain that requires consistency, scale-up can start to look fairly attractive.
CHY872 12y ago
Generally it's just that it's really difficult to do it right. Sometime's it's impossible. It's often loads more work (which can be hard to debug). Furthermore, it's frequently not even an advantage. Have a read of https://research.microsoft.com/pubs/163083/hotcbp12%20final.pdf https://research.microsoft.com/pubs/163083/hotcbp12%20final.... Remember corporate workloads frequently have very different requirements than consumer.
sgt101 12y ago
Oracle is incredibly well crafted for managing a transactional database in an enterprise setting. If it's $200k more and the option is to take a massive risk what would you do ? At some point the massive risk will become worth taking; this has happened for ETL and is on the way to happening for BI; there is a skills / tools gap but that will change.

SDGT 12y ago

The third and most important reason: They have someone to blame when shit goes tits up. Response time may still be abysmal, but "dammit we payed a million dollars for this!"

th3iedkid 12y ago
and one more thing with large volume transaction processing is scaling out on I/O and ETL jobs.Oracle (and other DB vendors) offer a lot of utilities that scale out perfectly with least of development time. For e.g. it would rather be a difficult deal to work with parsers to parse a Gigabit-data file with code we have to own up , than to use features these DBs directly offer to parallel-load into a ready to use table within minutes.

elliptic 12y ago

I'm not saying that Oracle hardware or software is the solution, but "scaling-out" is incredibly difficult in transaction processing. I worked at a mid-size tech company with what I imagine was a fairly typical workload, and we spent a ton of money on database hardware because it would have been either incredibly complicated or slow to maintain data integrity across multiple machines. I imagine that situation is fairly common.

AlisdairO 12y ago

Both, I suspect. When you consider the cost of engineer time needed to create high performance scale-out systems in a problem domain that requires consistency, scale-up can start to look fairly attractive.

CHY872 12y ago

Generally it's just that it's really difficult to do it right. Sometime's it's impossible. It's often loads more work (which can be hard to debug). Furthermore, it's frequently not even an advantage. Have a read of https://research.microsoft.com/pubs/163083/hotcbp12%20final.pdf https://research.microsoft.com/pubs/163083/hotcbp12%20final.... Remember corporate workloads frequently have very different requirements than consumer.

sgt101 12y ago

Oracle is incredibly well crafted for managing a transactional database in an enterprise setting. If it's $200k more and the option is to take a massive risk what would you do ? At some point the massive risk will become worth taking; this has happened for ETL and is on the way to happening for BI; there is a skills / tools gap but that will change.