pgDay Paris 4th edition happens March 15, 2018! And the Call for Papers is still open, as it closes with the year: the submission deadline is December 31st, 2017.
As I’ve been organizing the first edition of pgDay Paris back in 2015, this very conference is special to me! It’s been an amazing experience launching a new PostgreSQL conference…
Hats off to Magnus without whom the first edition would never have happened, and to Vik of course, who took over the organisation of the conference!
Florent Fourcot has read Mastering PostgreSQL in Application Development and has seen tremendous inprovements in his production setup from reading the first chapters and applying the book advices to his use case.
Here’s an interview run with Florent where he explains the context in which such improvements has been made!
The Enterprise Edition of Mastering PostgreSQL in Application Development ships with a docker image that hosts both a PostgreSQL server instance with a pre-loaded database, the one that’s used throughout the book examples, and also with a Jupyter Network notebook that hosts SQL queries thanks to the sql_magic plugin.
The PostgreSQL community made the explicit choice some times ago that they would not use the infamous master and slave terminology. Instead, the documentation introduces the concepts of High Availability, Load Balancing, and Replication with the terms Primary and Standby, and the even more generic term Replica is used in contexts when only the data flow is considered, rather than the particular role of a node.
Today I am very pleased to announce the release of the book Scaling Python from my good friend Julien Danjou!
As Julien says, Python applications can handle millions of requests. Well, we know here that it’s easier on them when they are using PostgreSQL of course!
In How to Write SQL we saw how to write
SQL queries as separate .sql files, and we learnt about using query
parameters with the psql syntax for that (:variable, :'variable', and
:"identifier").
For writing our database model, the same tooling is all we need. An important aspect of using psql is its capacity to provide immediate feedback, and we can also have that with modeling too.
