Writing a User-defined datatype

Walk-through of extending PostgreSQL with a user-defined type. The journey begins from the basics, from creating simple domain types over existing types, and continues to implementing a full-blown datatype from scratch in C.

PostgreSQL's advanced index types, GiST, GIN, and SP-GiST, are covered in enough detail to give an understanding of what each of them is good for. Support functions for each of them are shown for the example 'color' datatype.

GraphQL backend on PostgreSQL with plv8.

Recently, I was working on a project where graphQL was used for sending requests to its .NET Core backend, but this was not a good idea. The point is, a graphQL query is a hierarchical structure with a dynamic set of fields. It’s difficult to perform such requests via a statically-typed programming language and a relational database as suggested by the tools available. So, I came up with the idea of using the plv8 extension and perform graphQL queries right on the database side. It took me about two hours to develop a working prototype that could perform the same queries as the software under development for more than one month! Then various improvements have been made and I want to introduce them all. If you are thinking of using graphQL instead of REST, my speech could be most useful and could help you to save a lot of time.

High availability PostgreSQL cluster under the control of the Patroni for 1С. Single entry point is organized by Consul DNS on Windows

200 bases, several clusters, several terabytes of data Share our experience setting up and using patroni cluster DBMS Cluster on Linux, 1C server for windows. We use: PostgreSQL assembly for 1C, Patroni, Consul, Consul dns, Commvault, Ansible Vagrant file and Ansible playbook with roles attached.

Building protected databases using mandatory access control in PostgreSQL

Role-based access control (RBAC) is one of the main mechanisms used for access control in many DBMS, including PostgreSQL. This model is a sub-type of traditional discretionary access control with its restrictions. In addition to DAC, many operating systems also use mandatory access control (MAC) based on security labels. This additional security mechanism is obligatory for protecting information that demands higher levels of security. Naturally, we would like to use MAC within DBMS when working in OS with mandatory access control switched on.
In this talk, we'll give an overview of existing MAC implementations in DBMS, as well as share our approach to using security mechanisms provided by SELinux, the sepgsql extension for PostgreSQL, and the standard mechanism of row-level security (RLS), which has been available in PostgreSQL starting from version 9.5.
In our presentation, we will use the "Airlines" demo database provided by the Postgres Professional company to show how to protect sensitive information and personal data, compare different ways of storing security labels, and assess performance of our solution.