A retrospective look at the statistics

To build a decent query plan, the optimizer has to understand statistical characteristics of underlying data. It is interesting to observe how the structure of the collected information became more complicated over time: what the optimizer relied on back in its early days and what is at his disposal now with the release of the 12th version. We will also talk about how and when statistics are collected, how to manage this process and whether it is necessary to think about it at all.

Using a GiST index in solution of custom search problem

I'll show an example of solving the problem of searching "similar" texts for one given text in big array using GiST index. The problem itself is not much important, but it is easy to understand. Using this problem as example, I'll show one of many methods of adapting GiST index for custom search problems. Maybe this talk will help you to solve other search problems.

How to access your cloud PostgreSQL servers from highly secured corporate environment.

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.

To Eat "the Elephant" in chunks: how we made friends with MSSQL, Postgres, wrote our replication, and transferred to Postgres one of the largest MISes in Russia.

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.