Category “YeSQL” — 77 articles

Let’s continue to dive in PostgreSQL Concurrency. Last week’s article PostgreSQL Concurrency: Isolation and Locking was a primer on PostgreSQL isolation and locking properties and behaviors.

Today’s article takes us a step further and builds on what we did last week, in particular the database modeling for a tweet like application. After having had all the characters from Shakespeare’s A Midsummer Night’s Dream tweet their own lines in our database in PostgreSQL Concurrency: Data Modification Language, it’s time for them to do some actions on the tweets: likes and retweet.

Of course, we’re going to put concurrency to the test, so we’re going to have to handle very very popular tweets from the play!

PostgreSQL is a relational database management system. It’s even the world’s most advanced open source one of them. As such, as its core, Postgres solves concurrent access to a set of data and maintains consistency while allowing concurrent operations.

This article is a primer on PostgreSQL Isolation and Locking properties and behaviors. You might be interested into the previous article in the series: PostgreSQL Concurrency: Data Modification Language.

PostgreSQL is a relational database management system. It’s even the world’s most advanced open source one of them. As such, as its core, Postgres solves concurrent access to a set of data and maintains consistency while allowing concurrent operations. Postgres exposes its concurrency APIs in the SQL language, in particular in the DML parts of it: you can read the Data Manipulation Language chapter of the PostgreSQL docs for all the details.

Today it’s time to conclude our series of PostgreSQL Data Types articles with a recap. The series cover lots of core PostgreSQL data types and shows how to benefit from the PostgreSQL concept of a data type: more than input validation, a PostgreSQL data type also implements expected behaviors and processing functions.

This allows an application developer to rely on PostgreSQL for more complex queries, having the processing happen where the data is, for instance when implementing advanced JOIN operations, then retrieving only the data set that is interesting for the application.

Continuing our series of PostgreSQL Data Types today we’re going to introduce the PostgreSQL Point type.

In order to put the Point datatype in a context where it makes sense, we’re going to download a complete geolocation data set and normalize it, thus making good use of both the normalization good practice and those other PostgreSQL data types we’ve been learning about in the previous articles of this series.

Buckle-up, this is a long article with a lot of SQL inside.