Many organizations need to store time series data. Storing time series data in Amazon Relational Database Service (Amazon RDS) for PostgreSQL is a good choice if it needs to be joined with transactional data already in PostgreSQL. By nature, time series tables grow continuously. When tables get large, partitioning them will improve database performance and make maintenance much easier. In this webinar, dive deep into the benefits of using pg_cron and pg_partman on RDS for PostgreSQL, how to partition using the extensions, and other use cases where these extensions can be helpful.
Learning Objectives:
* Objective 1: Learn about the pg_cron and pg_partman extensions.
* Objective 2: Learn how to partition your PostgreSQL tables to improve database performance.
* Objective 3: Learn about other use cases for these extensions.
***To learn more about the services featured in this talk, please visit: https://aws.amazon.com/rds/postgresql/
****To download a copy of the slide deck from this webinar visit: https://pages.awscloud.com/Automatica... Subscribe to AWS Online Tech Talks On AWS:
https://www.youtube.com/@AWSOnlineTec...
Follow Amazon Web Services:
Official Website: https://aws.amazon.com/what-is-aws
Twitch: / aws
Twitter: / awsdevelopers
Facebook: / amazonwebservices
Instagram: / amazonwebservices
☁️ AWS Online Tech Talks cover a wide range of topics and expertise levels through technical deep dives, demos, customer examples, and live Q&A with AWS experts. Builders can choose from bite-sized 15-minute sessions, insightful fireside chats, immersive virtual workshops, interactive office hours, or watch on-demand tech talks at your own pace. Join us to fuel your learning journey with AWS.
#AWS
Watch video Automatically managing partitioned data on Amazon RDS for PostgreSQL- AWS Online Tech Talks online without registration, duration hours minute second in high quality. This video was added by user AWS Developers 18 October 2022, don't forget to share it with your friends and acquaintances, it has been viewed on our site 3,222 once and liked it 37 people.