PGConf.Russia 2018

This talk will compare architectural decisions that are made in PostgreSQL vs. ORACLE and will provide a closer look at the following components of both DBMSs:

1. The ins and outs of the working DBMS, its processes and their function
2. Structures that DBMS manages
3. Durability mechanics of each respective DBMS
4. MVCC design and database restoration options
5. Storage of data on the physical media

Each architectural decision will be evaluated based on the experience with DBMS of choice, ease of administration and future improvement possibilities.

This review will demonstrate the notable strengths of PostgreSQL as an open-source DBMS compared to the commercial solution in many cases.

This talk will be interesting for:

• PostgreSQL users, as it will allow to take a closer look into an alternative DBMS;
• PostgreSQL administrators, that will be able to see huge administration possibilities that ORACLE offers and that could be adopted in PostgreSQL;
• PostgreSQL hackers, as Postgres is being actively developed and this talk will review new development segments;
• Those who are willing to migrate from ORACLE (or any other commercial DBMS) into an open-source project, as this talk will show the features of PostgreSQL compared to the commercial product.

For the majority of System Administrators and DBAs performing an upgrade for RDBMS, let alone a major one, is a pain. That’s because one of the key factors that plays a role in a decision if and when to perform an upgrade is the downtime that it might come to during the process. This is true for any databases but especially important for those that are in production or under a high load.

Often, a major upgrade get’s cancelled and a DBA needs to go back to an older version due to the lack of experience or some basic errors that could have been easily avoided at the planning stage.

In our consultancy, we perform upgrades for our clients regularly and it allowed us to streamline the process and take some preventative measures that help us to perform it quickly, efficiently and with minimal or no downtime.

In this talk, I will share some key steps and tools that will help any DBA to become better at major upgrade performance. I will answer the following questions:

How to prepare for an upgrade of PostgreSQL? What one needs to do at the planning stage? How to plan your actions during the actual upgrade process? How to perform an upgrade successfully without going back to the older version? What actions one must perform following an upgrade?

I will also go through the two most popular processes of an upgrade: pg_upgrade и pg_dump/pg_restore, will compare some of the benefits and downfalls using each of these. I will also discuss some of the main issues one might face throughout the process and ways to avoid them.

This talk would be of interest to those who are new to PostgreSQL, as well as experienced DBAs who would like to learn more about upgrades or those who, in general, would like to understand why major upgrades should NOT be avoided like the plague.

Many of us know that it is MVCC that provides concurrency access to data in many relational databases that guarantee transactions consistency and isolation. But only deep understanding of the implementation of this mechanism in PostgreSQL allows us to better understand the processes in the database, to design the application logic and table structures to be the most effective in a high-load world. We'll take one of the processes in our product to understand how MVCC is implemented in PostgreSQL and we'll explain one of the peculiarity when seemingly unrelated activities can affect each other.

PostGIS is a spatial extension to PostgreSQL that enables spatial datatypes, access methods and a set of functions to perform geometric operations on them.

Typically PostGIS is used to select a small subset of a big static dataset. In this talk I'll cover issues that arise when working with big dynamic data flows, and ways to resolve them, on examples that we've met developing Juno ride sharing service backend.