PgConf.Russia 2020

A brief story how MySQL → PG migration could increase company efficiency tenfold times:

1. Program code has been reduced 50 times, with optimization of backend team (from 15 to 3 engineers)
2. Software development of new features has become measuring in days, not in months
3. Infrastructure costs per 1M users have been reduced 20 times
4. Database structure and technical documentation were simplified significantly, from 100K high-dependent tables to just 20 simple tables
5. New security level because of total forbidden on external SQL commands to the database
6. Quick analytics aggregation on multiple parameters, without external analytics systems
7. The last, but not the least: the main business was keeping alive during migration

Odd things in query plan analysis - wasted time and "unnecessary" buffers.
Structural hints in a plan. How to help a developer with optimization without writing a single line of code. How to match plan nodes with query text and take advantage of this information.

We will discuss stored procedures and functions, as well as the code within the database in general. We'll take a look at stored procedures from different angles: as a DBA, a database developer, and a backend developer. We will try to understand the specifics of stored procedures that often go against the common coding guidelines, and discuss best practices for working with stored procedures.
This is mainly a motivational talk for database and backend developers, not an advanced tech talk.

If you care about Postgres performance, there are a number of hardware acceleration options to help with different use cases. Intel Optane DC persistent memory creates new tier in data hierarchy allowing developers to utilize performance of traditional memory combining with volume and persistency of block storage devices. Unlike traditional DRAM-only in-memory systems, where memory is small, expensive, and volatile, Intel Optane DC persistent memory makes it possible to run larger Postgres databases (terabytes) in memory for higher performance. FPGAs are integrated circuits that can be reprogrammed dynamically to accelerate a specific workload such as SQL execution and data compression. FPGA accelerators extend Postgres with hundreds of SQL reader and writer processes that work in parallel on the FPGA. It’s similar to adding hundreds new cores to boost parallel processing on your server.