Introducing Crunchy Data Warehouse: A next-generation Postgres-native data warehouse. Crunchy Data Warehouse Learn more
Kat Batuigas
Kat Batuigas
This post is the second in a two-part series -- read the first here: Going Back to Basics with PostgreSQL Data Types . In my last post, I shared some interesting (and at times surprising) things that I learned while digging into data types in PostgreSQL. Data types like numeric, integer, date, and char/varchar exist in every other relational database system since the need to work with such data is pretty much a given. The implementation may vary somewhat between systems, but generally there are...
Read MoreKat Batuigas
Kat Batuigas
When I first started to learn how to code, I was introduced to the concept of data types: a 6 is not the same as "6", because the former is numeric (typically an integer type, with some variations in terminology based on the language) and the latter a string; "true" is not necessarily the same as true, because true can be a Boolean value in some languages. Underneath the code, these pieces of data are really just a combination of ones and zeros, but declaring their types allows them to play a pa...
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Kat Batuigas
In our last blog post about pg_featureserv , we showed how it can publish spatial datasets and access them via simple web requests. In this post, we’re going to discuss how publishing PostgreSQL / PostGIS functions via pg_featureserv provides even more flexible access to your data. A powerful feature of PostgreSQL is the ability to create user-defined functions . Functions let you wrap complex logic within a simple interface: passing in arguments, and getting back a set of values as output...
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