Shayon Sanyal
Principal WW PostgreSQL Specialist Solutions Architect at AWS
Shayon is a database architect specializing in PostgreSQL and AI/ML applications. With extensive experience helping enterprises implement vector search, agentic AI systems, and hybrid search architectures, he focuses on practical patterns that work at production scale. A regular speaker at database conferences, Shayon is passionate about making PostgreSQL's advanced capabilities accessible to the broader community.
Upcoming presentations
Building Agentic AI Applications with PostgreSQL as the Backbone
Memory systems, tool registries, MCP integration, and guardrails for production agents
The AI landscape is shifting from chatbots to autonomous agents—systems that plan, use tools, maintain memory, and take actions. While attention focuses on language models, the real differentiator for production agents is the data layer. PostgreSQL, with its combination of relational integrity, vector search, and extensibility, is emerging as the ideal backbone for agentic AI.
This session e...
Hybrid Search in PostgreSQL: Combining Vector and Full-Text for Real-World Applications
Reciprocal Rank Fusion, schema design, and query patterns for multi-modal search
PostgreSQL has evolved into a multi-model database capable of handling diverse search requirements. While many developers know about pgvector for semantic search or tsvector for full-text search, few have explored combining these capabilities into unified hybrid search systems. This session takes a practitioner's approach to building hybrid search in PostgreSQL. We'll start with the "why": sema...
Past presentations
Replacing Oracle’s Advanced Features in PostgreSQL: High Availability, Advanced Functions, and Extensibility
Who needs Oracle when you have PostgreSQL?
Migrating from Oracle to PostgreSQL often raises questions about replacing powerful Oracle features like Materialized Views, Flashback Queries, Virtual Columns, Oracle RAC, and PL/SQL Packages. While PostgreSQL doesn’t replicate these features identically, it offers robust alternatives that meet—and often exceed—Oracle’s capabilities.
This session will guide you through: - Replacing Oracle’...
Enhancing OLTP Systems with pgvector: Best Practices in Database Design
Generative AI and PostgreSQL
The integration of pgvector into existing Online Transaction Processing (OLTP) systems represents a significant advancement in leveraging vector search capabilities within traditional database environments. This presentation is designed to educate database professionals on the thoughtful integration of pgvector into OLTP applications powered by PostgreSQL, ensuring enhanced functionalities with...
Apr 18 2024
Using Global database in Amazon Aurora PostgreSQL
Using Global database in Amazon Aurora PostgreSQL
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...
Apr 8 2022
Amazon Aurora Global Database Design Patterns for HA and DR
Amazon Aurora Global Database Design Patterns for HA and DR
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 from region-wide outages. In this session, learn about the several use-cases and design patt...
Apr 8 2022