Reliable implementation of complex business logic with pgpro_scheduler
The pgpro_scheduler extension has an interesting but little-known feature - one-time jobs. Despite its simplicity, this feature can be used for complex transaction processing. On the one hand, it helps to reliably execute tasks taking a very long time, on the other hand, it ensures app scaling if certain conditions are met.
Nikita Levchenko ПАО «Ростелеком»Yuriy Plotnikov ООО «РТК ИТ»
We'll discuss our approaches to picking technical solutions for the systems we design. We'll consider their advantages and limitations. We'll share the facts about the changes in our engineering culture when import substitution requirements came into effect. We migrated the system with a classical three-tier architecture from Oracle to Postgres Pro DBMS. In my presentation I'll pay attention to data migration tools and peculiarities of development Java/Kotlin apps and SQL interoperability between two DBMSs.
Igor Kosenkov Postgres Professional
Everyone knows very well what a failover cluster PostgreSQL is and how such a cluster protects against failures within the same data center. However, recently, more and more enterprises have placed increased demands on their services, these requirements include disaster tolerance. We call such clusters a GEO-Cluster (KUK). In the report, I will talk about the varieties, principles and approaches to building GEO-Clusters PostgreSQL based on the Corosync/Pacemaker cluster software.
Tatiana Krupenya DBeaver CorpSergey Rider DBeaver Corp
What can be more important in the data load process than speed? Data migration is one of the most requested features in DBeaver. So the performance issue was highly important for us, in regard to PostgreSQL, as well as Greenplum, Redshift and other Postgres-based databases. We are ready to share our tiny secrets about 10x, 100x, 1000x, and even 10,000x performance improvements for data imports without any magic.
Anton Doroshkevich ИнфоСофт
Data is getting bigger, disks are getting faster, the DBMS optimizer is getting smarter, but the problem of " bloating " remains extremely relevant. I want to share my experience and approach to dealing with this effect on a large number of tables and data in them.