Structured query language (SQL) is now 50 years old. The original paper for SQL (then called SEQUEL) was published in May 1974 by Raymond Boyce and Donald Chamberlin, and provided a guide for data manipulation based on a set of simple commands. Today, we take SQL for granted around data – it is still the third most popular language used by professional programmers, and it can support innovations from geographic data through to JSON and generative AI.
But why is SQL still around? Why does this india whatsapp number data language, with its idiosyncrasies, quirks, and challenging syntax, still play such a central role in how we work around data today?
Successful SQL
To start with, we have to look at why SQL succeeded in its mission around data management and manipulation. At the time, data was a precious commodity, but using it effectively was hard. The standardization that SQL provided – and still provides today – just did not exist. SQL’s approach – while it might look clunky to a modern developer audience that is used to low-code and graphical user interfaces – was an effective and understandable way to interact with data. SQL is also based on solid mathematical models. This is what made it so effective in handling data to start with, but those solid underpinnings have kept it reliable to this very day.