It's not necessarily done in the db. As you suggested that's expensive. Although db might be a backing store, likely a more efficient mechanism is used to accompany the polling operation like storing the real-time status in memory in addition to finally on the db. You can poll memory much more efficiently than SELECT status from Table every second.
Also as I mentioned in a comment, in some circumstances, you can get a lot of mileage out of forging the appearance of status update through animations and such, employ estimation, checking the data source less often.
Edit
(an optimization to use less db resources for real time)
Instead of polling the database per user to check job status every X seconds, slightly alter the behaviour of the situation. Each time a job is added to the database, read the database once to put meta data about all jobs in the cache. So , for example, memory cache will reflect [user49 ... user3, user2, user1, userCurrent] 50 user's jobs if 1 job each. (Maybe I should have written it as [job49 ... job2, job1, job_current] but same idea)
Then individual users' web pages will poll that cache which is always kept current. In this example the db was read just 50 times into the cache (once per job submission). If those 50 users wait an average 1 minute for job processing and poll for status every second then user base polls the cache a total of 50 users x 60 secs = 3000 times.
That's 50 database reads instead of 3000 over a period of 50 min. (avg. one per min.) The cache is always fresh and yet handles the load. It's much less scary than considering hitting the db every second for each user. You can store other stats and info in the cache to help out with estimation and such. As long as fresh cache provides more efficiency then it's a viable alternative to massive db hits.
Note: By cache I mean a global store like Application or 3rd party solution, not the ASP.NET page cache which goes out of scope quickly. Caching using ASP.NET's mechanisms might not suit your situation.
Another Note: The db will know when another job record is appended no matter from where, so a trigger can init the cache update.
Despite a good database solution, so many users polling frequently is likely to create problems with web server connections and you might need a different solution at that level, depending on traffic.