I have had the misfortune of working with PostgreSQL for the last 8 months. Working is a relative term, for me little work has been done mostly I’ve been kicking off queries waiting forever fo the returns and then trying to run down the bottleneck.

I am not a Linux professional and have to rely on those professionals to diagnose what’s going on with the AWS instance that runs PostgreSQL 9.3. Everyone who looked at the situation has had a different opinion. One person looked at one set of performance data and said the system isn’t being utilized at all, someone else would say it’s IO bound, still someone else would say it’s the network card… So we wnet through all these suppositions added more RAM, then more processors, then we used the SSD drives more, finally switching from Non-provisioned IOPS to Provisioned IOPS got the system roughly as far as we could push it to where the complex queries would drive one CPU Core to 100%.

Now those of you who work with read enterprise RDBMS might say, “Wait… One CPU core reached 100%?” Well yes, of course, because you see PostgreSQL does not have parallel processing. Yeah…

No matter how many CTEs or sub queries present in a query statement sent to PostgreSQL, The processing of said query will happen in a synchronous, single threaded fashion on CPU core. I’m thinking SQL Server had parallel processing in the late 90’s or early 2000’s? It’s 2014 for crying out loud.

And it gets better! According to my observations, the Postgres process is also single threaded. This process is responsible for writing to the transaction logs. So there isn’t any benefit to create multiple log files for software striping and efficient log writing. In fact, one big insert seemed to back up all the smaller transactions, while the first insert wrote to the transaction log.

This is one of the joys of Open Source offerings. If the development community doesn’t think a feature is important you have to fork the code and write the feature yourself. What blows me away is that companies are willing to gamble the success of their products and implementations on something so hokey.