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.

Postgres has always had strong support for relational storage. However, there are many cases where relational storage is either inefficient or overly restrictive. This talk shows the many ways that Postgres has expanded to support non-relational storage, specifically the ability to store and index multiple values, even unrelated ones, in a single database field. Such storage allows for greater efficiency and access simplicity, and can also avoid the negatives of entity-attribute-value (eav) storage. The talk will cover many examples of multiple-value-per-field storage, including arrays, range types, geometry, full text search, xml, json, and records.

Sometimes it maybe a very tricky just to establish a connection with your remote database. Especially if your working place is in highly secured corporate environment and your database server is in highly secured remote cloud.

We will talk about bypassing SSH, SSL, jump servers, proxy servers, VPNs and various SSO (Kerberos/SSPI/LDAP/Active Directory) authentication systems in order to access your PostgreSQL database using console or rich UI interface and JDBC. We will describe different use cases - from trivial and typical to insane and over-secured.

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.