PgConf.Russia 2020

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.

MobilityDB is an open source moving object database system (https://github.com/ULB-CoDE-WIT/MobilityDB). Its core function is to efficiently store and query mobility tracks, such as vehicle GPS trajectories. It implements the Moving Features specification from the Open Geospatial Consortium (OGC). MobiltyDB is engineered up from PostgreSQL and PostGIS, providing spatiotemporal data management via SQL. It thus integrates with the postgreSQL eco-system allowing for complex architectures such as mobility stream processing and cloud deployments.

The presentation will explain the architecture of MobilityDB, its database types, indexes, and operations. We will highlight the PostgreSQL features that enable this extension, and the would like to have features. This presentation will be of special interest to the PostgreSQL community, and to professionals in the transportation domain.

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.

You will have a fascinating journey through PostgreSQL settings. We will talk about that with 1C not so or on the contrary so that under it it is necessary to adjust specially DBMS. We will discuss approaches to testing the speed of 1C. Consider the various options for backup schemes and fault tolerance. In the process, we will compare the speed of 1C on PostgreSQL configured by default with the speed of 1C configured for PostgreSQL. Also, we will create a replica of PostgreSQL, and switch to it the 1C Server "live", see what users will see 1C during this operation. And a separate block will be devoted to Postgres Pro Enterprise Edition, how the use of its advantages affects the speed of 1C.