PgConf.Russia 2020

In my talk, I will tell how we built a geographically distributed system of personal data storage based on Open Source software and PostgreSQL. The concept of the inCountry business is to provide customers with a ready-to-use infrastructure for personal data storage. Our business customers are ensured that their customer’s personal data is securely stored within their country’s borders. We wrote an API and SDK and built a variety of services. Our system complies with generally accepted security standards (SOC Type 1, Type 2, PCI DSS, etc.). We built our infrastructure with Consul, Nomad, and Vault, used PostgreSQL, ElasticSearch as a storage system, Nginx, Jenkins, Artifactory, other tools to automate management and deployment. We have assembled our development and management teams - DevOps, Security, Monitoring, and DBA. We use both cloud providers and bare-metal servers located in different regions of the world. Development of the system architecture and ensuring the stability of the infrastructure, consistent and secure operation of all its components is the main task facing our teams.

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.

PostgreSQL built-in full text search gives unique possibilities inaccessible for external search engines, such as virtual or generated document search and search with access restrictions. I will talk about these and other features, full text search configuration, indexes, and highlight the latest advances and future expectations

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.