What is database throughput?

In general, when you're talking about the "throughput" of an OLTP database, you're talking about the number of transactions per second. How many orders can the system take a second, how many web page requests can it service, how many customer inquiries can it handle. That tends to go hand-in-hand with discussions about how the OLTP system scales-- if you double the number of customers hitting your site every month because the business is taking off, for example, will the OLTP systems be able to handle the increased throughput.

That is in contrast to OLAP/ DSS systems which are designed to run a relatively small number of transactions over much larger data volumes. There, you're worried far less about the number of transactions you can do than about how those transactions slow down as you add more data. If you're that wildly successful company, you probably want the same number and frequency of product sales by region reports out of your OLAP system as you generate exponentially more sales. But you now have exponentially more data to crunch which requires that you tune the database just to keep report performance constant.

Throughput doesn't have a single, fixed meaning in this context. Loosely, it means the number of transactions per second, but "write" transactions are different than "read" transactions, and sustained rates are different than peak rates. (And, of course, a 10-byte row is different than a 1000-byte row.)

I stumbled on Performance Metrics & Benchmarks: Berkeley DB the other day when I was looking for something else. It's not a bad introduction to the different ways of measuring "how fast". Also, this article on database benchmarks is an entertaining read.