PgConf.Russia 2020

In the report, we want to talk about the experience of migrating one large system from Oracle to PostgreSQL. The system itself was built on the PHP + Oracle stack; its distinguishing feature was that all business logic was implemented in PL / SQL code. In a DBMS, there are more than 3000 packages with 4-10 functions (procedures) in each. In PHP - more than 10,000 forms with inserts of anonymous blocks used to receive data, process and save results in Oracle.

To solve this extremely voluminous work, we took ANTLR4 (a powerful parser generator for reading, processing, executing, or translating structured text), PL/SQL grammar, and created an automatic converter that allows you to convert all objects in the schema and our system from Oracle to working code for 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.

It is our experience of the medical information system "RT MIS" transfer from MSSQL to PostgreSQL . When the necessity of transfer to PostgreSQL in our "RT MIS", one of the largest medical information systems, became imminent, we felt really terrified having assessed its amount: there was a huge number of stored procedures, functions, SQL-queries in its application code and services. It all requested transcribing, was exacerbated by demands on the system accessibility. So the variant "we awoke in the morning and PostgreSQL was working everywhere" was definitely impossible. That is why we chose another way: began eating "the elephant (PostgreSQL)" in chunks.

In my report, I am going to share our practical experience of the transfer, the instruments we used, the reason for another replication, the problems we met and their solutions. And finally, what turned out to be better: PostgreSQL or MSSQL.

Patroni and Stolon are two of the most popular and advanced solutions for orchestrating PostgreSQL and ensuring auto-failover for clusters with the Leader-Followers configuration. However, engineers who migrate from good old tools like Corosync&Pacemaker or built-in solutions of other DBMS often run into issues when installing these tools and figuring out the purpose of each component.
In this tutorial, we will go through a typical installation procedure of Patroni and Stolon clusters on virtual machines (not in containers), as well as review their behavior in case of various infrastructure failures. The whole process will be demonstrated on three vagrant virtual machines with pre-built images. You can follow along on your own system if you set up the required environment.