PgConf.Russia 2020

An enterprise-grade PostgreSQL requires many complementary technologies to the database core: high availability and automated failover, monitoring and alerting, centralized logging, connection pooling, etc. That is, a stack of components around PostgreSQL. Kubernetes has enabled a new model to deploy software abstracting away the infrastructure. However, containers are not lightweight VMs, and the packing of software paradigms that work on VMs are not valid on containers/Kubernetes. How should be PostgreSQL and its stack be deployed on Kubernetes? Enter StackGres. An open source software that is the result of re-engineering PostgreSQL to become cloud native. Join this talk to learn and see demos of how to generate PostgreSQL minimal containers; how the sidecar pattern is used (abused) to integrate PostgreSQL’s stack components, and how the networking and storage are handled. More info: stackgres.io.

The story about powering a 1.5 petabyte analytics application with 2816 cores and 18.7 TB of memory in the Citus cluster at the Microsoft. The Windows team measures the quality of new software builds by scrutinizing 20,000 diagnostic metrics based on data flowing in from 800 million Windows devices. At the same time, the team evaluates feedback from Microsoft engineers who are using pre-release versions of Windows updates. At Microsoft, the Windows diagnostic metrics are displayed on a real-time analytics dashboard called “Release Quality View” (RQV), which helps the internal “ship-room” team assess the quality of the customer experience before each new Windows update is released. Given the importance of Windows for Microsoft’s customers, the RQV analytics dashboard is a critical tool for Windows engineers, program managers, and execs.

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.

Greenplum is a horizontal scalable database based on PostgreSQL core. It is used for OLAP workloads and a standard task is to quickly load or unload large amounts of data. The external data resources are usually another distributed systems. In this talk I will show how Greenplum can work with external data. What is the architecture and performance of external and foreign tables and how to handle streaming data. What will be changed in the next version. The examples of Kafka and ClickHouse connectors development.