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Over the years I have discussed the issue of Postgre SQL vs. Unless otherwise stated I am referring to Postgre SQL 9.3 and MS SQL Server 2014, even though my experience with MS SQL Server is with versions 2008 R – for the sake of fairness and relevance I want to compare the latest version of Postgre SQL to the latest version of MS SQL Server.Where I have made claims about MS SQL Server I have done my best to check that they apply to version 2014 by consulting Microsoft's own documentation – although, for reasons I will get to, I have also had to rely largely on Google, Stack Overflow and the users of the internet.
CSV is the de facto standard way of moving structured (i.e. All RDBMSes can dump data into proprietary formats that nothing else can read, which is fine for backups, replication and the like, but no use at all for migrating data from system X to system Y.
Anyone who follows developments in IT knows that cross-platform is a thing now.
Cross-platform support is arguably the killer feature of Java, which is actually a somewhat lumpy, ugly programming language, but nonetheless enormously successful, influential and widespread.
The whole thing took perhaps 100 lines of code and three hours – two of which were spent getting to grips with SWIG, which was new to me at the time).
If you don't believe me, download this correctly-formatted, standards-compliant UTF-8 CSV file and use MS SQL Server to calculate the average string length (i.e.
Each of these things, in isolation, may seem like a relatively minor niggle; however, the overall effect is that getting real work done in MS SQL Server is harder and more error-prone than in Postgre SQL, and data analysts spend valuable time and energy on workarounds and manual processes instead of focusing on the actual problem.
Update: it was pointed out to me that one really useful feature MS SQL Server has which Postgre SQL lacks is the ability to declare variables in SQL scripts. I wish it could, because there are an awful lot of uses for such a feature.Let's not understate this: a data analytics platform which cannot handle CSV robustly is a broken, useless liability. The commands support the spec outlined in RFC4180 (which is the closest thing there is to an official CSV standard) as well as a multitude of common and not-so-common variants and dialects. When an error occurs, they give helpful error messages.Importantly, they will not silently corrupt, misunderstand or alter data.If I find out that I've got something wrong, I'll fix it.I am comparing the two databases from the point of view of a data analyst.Microsoft no longer has the monopoly it once enjoyed on the desktop, thanks to the rise of Linux and Apple.