SQL how unloved it must feel sometimes, constantly being maligned, accused of being on the wrong side of the object-relational impedance mismatch, lacking the glamour of OO programming languages that claim the moral high ground. Yet at the same time hewing and hauling most of the world’s structured data on its old but well fashioned back.
SQL is perhaps the world’s most popular DSL, a declarative language for the manipulation of tabular data, easy to learn yet capable of powerful (and sometimes complex) expressions. And like the Ronseal ad, a SQL statement no matter how simple or complex, does exactly what it says, all the complexity of loops and iterations and the attendant errors, abstracted away, it just works!
SQL is both a programmer and an end-user tool; after Excel formulas, it’s the language most likely to be understood and used by “civilians”. There are few enough such cross-over tools, so think twice before building a datastore that doesn’t offer a SQL API. And I guess that’s what Amazon did. Although SimpleDB is not a relational database, they’ve decided to add a SQL API, following Google’s lead with its SQL front-end to the non relational big-table backed Google App datastore.
SQL is also the reason why I’ve integrated SQLite with Excel , leveraging SQL to manipulate tabular data with greater efficiency and fewer errors while still keeping the touchy-feely power of Excel. I expose SQLite to Excel via UDFs rather than menu options or wizards, so that the transformation logic is visible and approachable (at least to those comfortable with excel formula “programming” and with basic SQL).
SQL is my weapon of choice because of my belief in the primacy of data. It is data that matters in the long run, not the algorithms or GUIs that temporarily use (and abuse) it. In my time in Guinness Ireland I had the task of transferring master and historical transactional data from “legacy systems” into SAP ,Siebel and a new datawarehouse; data that had a decade and a half earlier been transferred by me into those same legacy systems from even older systems. In fact, the data’s electronic lineage could be traced back to a 1960’s era ICL mainframe (I have the original spec!) and I’m sure it existed in accountancy machine punch-cards prior to that. Understand a business’s data and you’ll not just understand the business as it currently operates but also how it operated in the past and its future potential.
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