I just came across this post from the high scalability blog.
I just want to say what the nosql movement gave me back.
We just finished writing a new application which visualizes pseudo realtime analytics information, it’s a web application, most of our analytics data is stored in hadoop, for this web app we decided to use mysql.
Hive wouldn’t be appropriate given its response time to execute a query (and lots of map reduce indeed), so we do get the data from hdfs on an hourly basis and store it in mysql.
After a quick spike on hbase we picked up mysql because we needed group by semantics, but at the same time we started using mysql in a different way, we don’t have any relations, we don’t do joins, we store our data as in a big table.
So basically we use the best of both words: no relations but sql.
This db grows pretty fast, the application has been running fully operational live for less than a day now and the total db size (two tables) it’s 48GB.
Then, for once, I came out with a good idea, we split the big table in a dozen of other smaller tables, basically the analytics source regions, what before was a column and a where clause in our queries became just a suffix of the original table.
I’ve been strongly inspired by the way hadoop manages partitions.
In conclusion that’s what the noSQL movement gave me back: he made me think differently to common data problems.