Curt Monash has a great post describing eight kinds of analytic DBMSes. Here's a picture that presents a simplified view, but I highly recommend the original post. There are three major groups: the big enterprise data warehouses (EDWs), various kinds of data marts, and what he calls the "bit bucket" category -- which is where he places Hadoop. I've left out the "archival store" and the "operational analytic server" which was essentially a catch-all category.
Let's look at Hadoop and related technologies -- Monash argues that this is the "big bit bucket" category. A place to gather large amounts of data cheaply and do some analytics .This is the kind of data that you'd normally consider too low-value to justify putting it inside your gold-plated EDW. As Hadoop gets better at TCO, performance, and adds better support for reporting, high-level analytics, and workload management -- how is it going to affect the other spaces? I've argued before that Hadoop is not going to be the next platform for EDWs for a long time to come.
One way to look at an improved Hadoop is as a bigger, more reliable, lower cost player in the "large investigative data mart" space. The investigative analytics aspect is likely to be Hadoop's major advantage along with low cost. Cheaper storage, better programmability, great fault-tolerance, and eventually reasonably good efficiency is going to make for a very interesting entry in the "large investigative data mart" space.
Traditional data marts are really good at being a data mart! Hadoop is a long way off from competing with those -- but there is probably a segment of this market that values elasticity and low-cost. My guess is startups like Platfora are going to target this space. I suspect very high scale marts that are not very demanding when it comes to concurrency and performance will very soon be better served by Hadoop-based solutions.
The unlikely category of "outsourced data marts" is actually quite promising. As workload management improves, it might be possible to consolidate large outsourced marts for reporting on Hadoop. Individual marts that are > 20PB are unlikely to be a large enough market (at least, not in the short term), but businesses that offer analytics on large datasets -- advertising tracking, clickstream analytics for customer modeling, website optimization, etc -- they will probably want a highly scalable, elastic, multi-tenant, low-cost mart.