Slashdot Mirror
Why Some Devs Can't Wait For NoSQL To Die
theodp writes "Ted Dziuba can't wait for NoSQL to die. Developing your app for Google-sized scale, says Dziuba, is a waste of your time. Not to mention there is no way you will get it right. The sooner your company admits this, the sooner you can get down to some real work. If real businesses like Walmart can track all of their data in SQL databases that scale just fine, Dziuba argues, surely your company can, too."
So you're in surgery for 3 hours doing a kidney transplant, having used your trusty medium vascular clamp that have served you for the past 20 years. You're finally done and the patient is in recovery, so you sit down to relax with the latest copy of JAMA. They've got a great article about the latest development of Cardiac clamps, and you think to yourself "Why not use a heart clamp for kidney transplants!" Brilliant. So you order up some new clamps from MedicalClamps.com, and use them on your next patient. The surgery goes fine, but 3 months later the patient is back in your office with a failed kidney. You open 'em up, and it's obvious the clamp exerted too much pressure on the artery, damaging it in the process. Stupid carciac clamps! You're not a heart surgeon!
AccountKiller
Pretty sure he meant 1M page views/day as he compares it to slashdot using alexa data.... Is reading comprehension really that hard? Context clues are your friend.
I run a site using django/postgres, we do about 100k page views/day on a 512Mb 10GB Virtual machine. Its not doing anything crazy like google, but yeah, we aren't close to needing more power yet. When we do, first thing we'll do is bump up RAM for increased cache space...
Many of the NoSQL sources scale better than a normal database and are available cheap. Oracle costs a fortune, and if you want to run Oracle on a cluster good luck. They also don't let you publish benchmarks without their permission. But most people I know who use Oracle claim it totally beats everything else (without further clarification). DB2 includes a cluster edition that is also quite good. It uses a shared nothing architecture. But none of these solutions are free. Also teradata is also cited as a good parallel database. If you are a start-up and your choice is a NoSQL solution that is almost free or 100,000+ for some commercial parallel database, which do you go to?
But no matter what you will consume resources with a relationship database on ensuring consistency (which many times is what you want but not 100% of the time). Amazon's Dynamo works by not caring so much about consistency and trading consistency for availability of the overall service. For a shopping cart it is fine, but you wouldn't want to do your credit card processing using it. Google's GFS is optimized to do the file operations that google does the most. However there was an article in the ACM not that long ago comparing Map Reduce (Hadoop's implementation) against two parallel databases, and it lost. OF course the Parallel Databases were all not free....and hadoop is....
So overall I'd say the decision comes down to price mostly (as it does with most startups). If you can make do with one server than sure do PostgreSQL (or mySQL...although they always tried to force licensing for commercial products even though it is GPL...). If you need a cluster, both have clustering solutions, but as far as I can tell they are not as good as the commercial Parallel databases. If you have lots of money then sure go with Oracle, it seems through word of mouth Oracle is the best for both parallel and stand alone in terms of performance. DB2 was good enough for a former job. They had terabytes in the mid 1990's using about 20 servers. Now that the hardware is much better I'm sure it scales even better.... But if money is a consideration, then go with an open source noSQL solution. A lot of people now swear by Cassandra, I haven't had a chance to check it out yet.
Two orders of magnitude is not 20x, it's 100x.
And for non-intensive applications, that's still fine.
And SQLite isn't actually that slow anyway. It's comparable.