Using Global database in Amazon Aurora PostgreSQL
Presented by:
Shayon Sanyal
Shayon Sanyal is a Principal Worldwide Specialist Solutions Architect at AWS, where he is the global subject matter expert for Amazon Aurora PostgreSQL and leads the Agentic AI for Databases initiative. He works with enterprises to take vector search, hybrid retrieval, and agentic AI systems from prototype to production scale, including some of the largest pgvector deployments in existence, with over 100 billion embeddings on PostgreSQL. He authored the launch blog for pgvector on Aurora PostgreSQL and co-authors AWS case studies on billion-scale retrieval. A regular speaker at re:Invent, PostgresConf, Postgres Summit, and PGConf.EU, Shayon is passionate about making PostgreSQL’s advanced capabilities accessible to the broader community.
Sukhpreet Bedi
Sukhpreet is a Senior PostgreSQL Specialist Solutions Architect at AWS, where she specializes in Amazon RDS and Aurora PostgreSQL engines. As a trusted technical advisor, she guides organizations in building resilient and secure database architectures on AWS. Her expertise extends to implementing Agentic AI solutions on PostgreSQL, helping customers develop intelligent applications that transform their business capabilities through modern database technologies.
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An Amazon Aurora Global database is designed for globally distributed applications, allowing a single Amazon Aurora database to span multiple AWS Regions. It replicates your data with no impact on database performance, enables fast local reads with low latency in each Region, and provides disaster recovery (DR) from Region-wide outages. In this session, learn how to plan for cross-Region DR and easily scale Aurora reads across the world to place your applications close to your users. You also learn how to meet your recovery point objective (RPO) and recovery time objective (RTO) with Amazon Aurora global databases.
- Date:
- 2022 April 8 13:10 PDT
- Duration:
- 50 min
- Room:
- Ballroom
- Conference:
- Silicon Valley 2022
- Language:
- Track:
- AWS Data Day
- Difficulty:
- Medium