PgConf.Russia 2019

Python may not be the fastest programming language on the CPU, but its fast and easy development saves a lot of costs between the keyboard and the chair. Since database clients spend most of their time waiting for a response from the database server, Python's asynchronous functionality available in the recent versions (3.5+) may help to optimize the application's runtime considerably by working on something else while server's response is being prepared. The asynchronous interface between Python and PostgreSQL is called "asyncpg". In the workshop we'll explore this library and write a short application using some of its useful features.

At pgconf’17 I talked about our analytics systems based on PostgreSQL. Afterwards we looked at hadoop, s3, presto, vertica, and other frights. Finally we stopped to suffer nonsense and just completed PostgreSQL with ready Greenplum and Clickhouse. As a result, we achieved amazing performance, fast migration, easy maintenance, reliability and horizontal scalability. We enabled to recover the system after fault in two commands, decreased infrastructure costs and expanded functionality due to ANSI SQL, MPP and In-memory. All within the open-source and full SQL paradigm. We called the product GreenHouseSQL, which is our inner whole cycle data platform. In the talk we will show the beauty of solution internals, explain the advantages and flaws, tips and tricks of starting with Greenplum, as well as why do we need Clickhouse, what is left to PostgreSQL, and eventually how does it all work.

Our company has developed a software product Live Universal Interface (LUI) is a tool to quickly create and modify standardized on-screen forms to WEB browsers without compiling code, know just enough SQL. LUI is aimed at B2B, B2G, G2C and B2C segments and intended for use in billing systems, financial management, accounting and control of production, where you must decide first and foremost functional tasks, rather than demonstrate unnecessary graphics elements.

Collective elaboration is provided by storing all elements of program code in the total database, which can be located on the corporate server or in the "cloud" on a third-party site.

PostgreSQL provides possibility to create temporary tables. Though a temporary table is accessible only to a single session and is removed at the end of the session, all information about it is stored in the system catalogs of PostgreSQL. This is related to several issues, which make it difficult or impossible to use temporary tables in some cases. There are attempts to solve this feature, including in our company. But they have not yet succeeded, mainly because of the PostgreSQL engine. In the talk I want to tell about simple and small pg_variables extension. It allows you to create table variables along with scalar ones. I will tell how it can replace temporary tables, what advantages and disadvantages it has.