Migration from Oracle PL/SQL to Postgres pl/pgSQL: Two Years Later

In 2019 we migrated distributed railway application from Oracle 11g SE to vanilla PostgreSQL 11.9. Almost 2 years have passed, the system is working good. The report focuses on how we migrated, what problems we faced during this migration and after migration, as well as what we would have done differently today experience.

Future Postgres Challenges

Postgres has been a vibrant project for decades, and probably will be popular for decades to come. However, as with any complex endeavor, challenges are always lurking. This talk explores the many project, competitive, and technical challenges in the future that could derail its success. By exploring these challenges, we will be better able to avoid them.

Elegant K-nearest neighbor (KNN) searching in PostgreSQL

Finding the nearest neighbor can be required for various tasks. For example, when you need to find the closest object to a given point on the map. This task looks trivial to non-programmer (a person can easily cope with it if they have a map). In a software developer's reality, this task doesn't have a common solution available to everyone. To get rid of this headache, programmers often create ad hoc solutions also known as "crutches". These workarounds don't look nice and often ruin the mood of a creative programmer who needs to go to a beer pub to cope with the cognitive dissonance :)

Indeed, while a person has a typical field of view and a map with a certain scale, the programmer has only one given point and a huge number of other points (i.e. billions of stars). This multitude of points gets a lot of incoming requests, including the write requests, not just read ones. You can write a perfect query in SQL, however, the real-world query execution plan will be depressingly long. To find the closest neighbor, you will have to read the entire table, compute all the distances from the given point and return the given number of good enough results. Indexing doesn't help in this case, as you will have to fully scan the search tree and read the entire table in random order. This will take much longer than simple table reading. In reality, tasks, where you need to efficiently find nearest neighbors, aren't limited to spatial search. It can also be used for classification tasks, finding typos, data clustering, and deduplication. All such tasks will benefit from efficient nearest neighbor search in DBMSs that are now a de facto standard for storing the data. What do we mean by "efficient search"? It means that our search is fast, concurrent, scalable, and supports various data types (most likely, non-standard ones). We implemented such KNN search in PostgreSQL 11 years ago. I will cover its implementation, today's state and share some use cases for KNN.

Why Crew Resource Management in Database Teams

Crew Resource Management is a field which has become critical in many fields including aviation and nuclear power. However in IT, this field has not been well implemented. In this talk we will discuss what crew resource management is, what kinds of problems it solves, and why all database teams should implement it.

Several PostgreSQL-related case studies will be discussed and both technical and human factors will be part of the case studies.