Store and analyze petabyte-scale time-series data with PostgreSQL & TimescaleDB

• Postgres Conference Silicon Valley (In-Person):

https://postgresconf.org/conferences/SV2022

• Community Chat: https://discord.gg/bW2hsax8We

• Presented by: Ryan Booz

• RSVP: https://bit.ly/3tAHvrc

Time-series data is everywhere (really!), and it’s uniquely challenging for several reasons: it comes at an ever-increasing rate, is INSERT heavy, and often consumes lots of compute and storage resources that can be difficult to manage.

For the last decade, NoSQL databases have been many folks’ go-to technology for handling the deluge, but this came at the expense of efficient, relational queries. Being able to store this data in a relational database - and PostgreSQL in particular - empowers developers to gain powerful insights without having to build a bridge between the time-series data and the business-related data that you need to filter and report on.

In this webinar, we'll talk about what time-series data is, why you probably have a lot more than you realize, and the insights it helps you uncover about your projects, apps, users, organization, and beyond.

You’ll see how PostgreSQL and TimescaleDB solve common problems with storing and querying massive amounts of time-series data – all while using SQL and the Postgres tools and capabilities you know and love.

Because showing is better than telling, we’ll demo TimescaleDB features like native compression, continuous aggregates, specialized analytics functions, query planner enhancements, and more, and leave you with tips and resources to help you meet the demands of time-series workloads with ease.