PgConf.Russia 2020

When migrating data from one DBMS to another, the question arises: choose a third-party tool or to program the migration yourself? Companies, trying to grow competencies within themselves, choose the second option. And they come across the "invention of their own bicycles". However, the market has powerful free data migration tools. One such tool is Pentaho Data Integration, part of the Pentaho Community Edition. The report will discuss the use of this package for data migration between Oracle and PostgreSQL. Particular attention will be paid to the problems with using this tool, and to the tasks of testing for the completeness and integrity of migrated data.

Small video illustration:

Any DBA needs some kind of tool for historical workload analyse. Assume once at morning your monitoring team will report of sudden performance degradation at 2-3 a.m., and now you need to investigate this issue. What activities was most resource consuming within that hour? There are several tools for solving this problem, and I'll talk about one very easy and convenient tool - pg_profile. It need only a postgres database and a cron-like tool to run, and it will generate a workload profile report for your database as you need it. Ths report will be a good start point for further investigation.

Kubernetes is the new way of deploying software, programmatically, on almost any infrastructure (be it cloud or on-prem). But is a complex beast. How to get started? How to dive deeper? What are the specific best-practices and special hints for Postgres DBAs dealing with Kubernetes? Join this half-day tutorial to learn, practically, among other topics:

• How to quickly get started with Kubernetes
• Manage storage
• Manage services, networking and ingress/egress
• How to make Postgres cloud-native in Kubernetes
• Do a show-run of existing Postgres operators, including Zalando, CrunchyData and StackGres.

This tutorial is very practical. BYOL! (Bring Your Own Laptop). With Kubernetes installed! (check microk8s, minikube or k3s if you don’t have any installed.

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.