Raj Jayakrishnan

In recent years, vector search has emerged as a key tool for handling high-dimensional data, enabling applications like recommendation systems, semantic search, and AI-driven insights.

In the era of big data and data-driven decision-making, the ability to process large volumes of data efficiently has become a critical requirement for modern applications.

Do you deal with PostgreSQL query performance–related issues? In this code talk, explore advanced techniques for monitoring query plans in Amazon Aurora PostgreSQL-Compatible Edition and maintaining query plan stability using Aurora query plan management.

Extract: Understanding Database Statistics in PostgreSQL Understanding Database Statistics in Postgres Session Description Database statistics play a crucial role in optimizing query performance and overall database health in Postgres.

Amazon Aurora PostgreSQL-Compatible Edition supports Trusted Language Extensions (TLE) for PostgreSQL, which is an open source development kit for building PostgreSQL extensions and managing them from a SQL interface.

Amazon Aurora Serverless brings automatic scaling to MySQL and PostgreSQL, allowing applications to instantly scale to hundreds of thousands of transactions in a fraction of a second. This session will dive into the Aurora architecture that allows this to happen. Additional topics include...