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Schedule for Postgres Conference: 2026

Dev Postgres Extensions Day Essentials Ops Professional Development & Wellness Life and Fun Conference Happenings

	07: 00	07: 10	07: 20	07: 30	07: 40	07: 50	08: 00
Almaden Ballroom
Almaden Foyer
San Pedro (Level C)
Santa Clara (Level C)
Winchester
Winchester 2

	08: 00	08: 10	08: 20	08: 30	08: 40	08: 50	09: 00
Almaden Ballroom
Almaden Foyer				Registration
San Pedro (Level C)							Building Real-Time, Data-Aware Intelligence with Postgres & Model Context Protocol (MCP)
Santa Clara (Level C)							Autonomous PostgreSQL: When AI Agents Become Your DBA
Winchester							The power of mentorship
Winchester 2							Running PostgreSQL in Hybrid Data Architectures

	09: 00	09: 10	09: 20	09: 30	09: 40	09: 50	10: 00
Almaden Ballroom
Almaden Foyer	Registration
San Pedro (Level C)	Building Real-Time, Data-Aware Intelligence with Postgres & Model Context Protocol (MCP)						Using Postgres to locate the best coffee near you! ☕
Santa Clara (Level C)	Autonomous PostgreSQL: When AI Agents Become Your DBA						Elevate your DBA toolset with pg collector
Winchester	The power of mentorship						Implementing Transparent Data Encryption At Rest
Winchester 2	Running PostgreSQL in Hybrid Data Architectures			Materialized Views: Performance Shortcut or Operational Trap?			RDS Maintenance: Strategies for Patching and Version Upgrades

	10: 00	10: 10	10: 20	10: 30	10: 40	10: 50	11: 00
Almaden Ballroom
Almaden Foyer	Registration
San Pedro (Level C)	Using Postgres to locate the best coffee near you! ☕						YMatrix mxvector: How to implement high performance pluggable vectorized executor in PostgreSQL
Santa Clara (Level C)	Elevate your DBA toolset with pg collector						A benchmark study on the impact of PostgreSQL server parameter tuning
Winchester	Implementing Transparent Data Encryption At Rest						When a spreadsheet won't cut the mustard
Winchester 2	RDS Maintenance: Strategies for Patching and Version Upgrades						Defining success on your terms

	11: 00	11: 10	11: 20	11: 30	11: 40	11: 50	12: 00
Almaden Ballroom							Lunch
Almaden Foyer	Registration
San Pedro (Level C)	YMatrix mxvector: How to implement high performance pluggable vectorized executor in PostgreSQL			Debezium and PostgreSQL in Action
Santa Clara (Level C)	A benchmark study on the impact of PostgreSQL server parameter tuning
Winchester	When a spreadsheet won't cut the mustard			Vector Database Performance Challenges, A CaseStudy
Winchester 2	Defining success on your terms

	12: 00	12: 10	12: 20	12: 30	12: 40	12: 50	13: 00
Almaden Ballroom	Lunch
Almaden Foyer	Registration
San Pedro (Level C)							The Open Source Approach: Building Production-Ready AI Apps with Postgres
Santa Clara (Level C)							We are all the 99th percentile
Winchester							What Can An AI Assistant Do For You?
Winchester 2

	13: 00	13: 10	13: 20	13: 30	13: 40	13: 50	14: 00
Almaden Ballroom
Almaden Foyer	Registration
San Pedro (Level C)	The Open Source Approach: Building Production-Ready AI Apps with Postgres						From Transactions to Agents: PostgreSQL in Modern AI Applications
Santa Clara (Level C)	We are all the 99th percentile			YMatrix Domino: Design Considerations, Trade-offs, and Implementation of In-Database Stream Processing			The Elephant in the Room: Tackling PostgreSQL Major Version Upgrades Head-On
Winchester	What Can An AI Assistant Do For You?						PostgreSQL 18: The Evolution Continues — What’s New This Year
Winchester 2

	14: 00	14: 10	14: 20	14: 30	14: 40	14: 50	15: 00
Almaden Ballroom
Almaden Foyer	Registration
San Pedro (Level C)	From Transactions to Agents: PostgreSQL in Modern AI Applications			Building Durable Programs with Postgres			Building Agentic AI Applications with PostgreSQL as the Backbone
Santa Clara (Level C)	The Elephant in the Room: Tackling PostgreSQL Major Version Upgrades Head-On						Enhancing PostgreSQL Sharding Through Agentic AI: Scalability, Optimization, and Autonomous Management
Winchester	PostgreSQL 18: The Evolution Continues — What’s New This Year						Mastering PostgreSQL Partitioning: Advanced Questions and Demos
Winchester 2

	15: 00	15: 10	15: 20	15: 30	15: 40	15: 50	16: 00
Almaden Ballroom
Almaden Foyer	Registration
San Pedro (Level C)	Building Agentic AI Applications with PostgreSQL as the Backbone						Beyond Text: Building Multimodal Search with pgvector in PostgreSQL
Santa Clara (Level C)	Enhancing PostgreSQL Sharding Through Agentic AI: Scalability, Optimization, and Autonomous Management						Migrating Oracle RAC to PostgreSQL Using Ora2Pg
Winchester	Mastering PostgreSQL Partitioning: Advanced Questions and Demos						Intel® AVX-512 Accelerates PostgreSQL 18 CRC32C Checksums
Winchester 2

	16: 00	16: 10	16: 20	16: 30	16: 40	16: 50	17: 00
Almaden Ballroom
Almaden Foyer
San Pedro (Level C)	Beyond Text: Building Multimodal Search with pgvector in PostgreSQL
Santa Clara (Level C)	Migrating Oracle RAC to PostgreSQL Using Ora2Pg
Winchester	Intel® AVX-512 Accelerates PostgreSQL 18 CRC32C Checksums
Winchester 2

	17: 00	17: 10	17: 20	17: 30	17: 40	17: 50	18: 00
Almaden Ballroom
Almaden Foyer
San Pedro (Level C)
Santa Clara (Level C)
Winchester
Winchester 2

	18: 00	18: 10	18: 20	18: 30	18: 40	18: 50	19: 00
Almaden Ballroom
Almaden Foyer
San Pedro (Level C)
Santa Clara (Level C)
Winchester
Winchester 2

	19: 00	19: 10	19: 20	19: 30	19: 40	19: 50	20: 00
Almaden Ballroom
Almaden Foyer
San Pedro (Level C)
Santa Clara (Level C)
Winchester
Winchester 2

	07: 00	07: 10	07: 20	07: 30	07: 40	07: 50	08: 00	08: 10	08: 20	08: 30	08: 40	08: 50	09: 00
Almaden Ballroom
Almaden Foyer										Registration
San Pedro (Level C)													Building Real-Time, Data-Aware Intelligence with Postgres & Model Context Protocol (MCP)
Santa Clara (Level C)													Autonomous PostgreSQL: When AI Agents Become Your DBA
Winchester													The power of mentorship
Winchester 2													Running PostgreSQL in Hybrid Data Architectures

	09: 00	09: 10	09: 20	09: 30	09: 40	09: 50	10: 00	10: 10	10: 20	10: 30	10: 40	10: 50	11: 00
Almaden Ballroom
Almaden Foyer	Registration
San Pedro (Level C)	Building Real-Time, Data-Aware Intelligence with Postgres & Model Context Protocol (MCP)						Using Postgres to locate the best coffee near you! ☕						YMatrix mxvector: How to implement high performance pluggable vectorized executor in PostgreSQL
Santa Clara (Level C)	Autonomous PostgreSQL: When AI Agents Become Your DBA						Elevate your DBA toolset with pg collector						A benchmark study on the impact of PostgreSQL server parameter tuning
Winchester	The power of mentorship						Implementing Transparent Data Encryption At Rest						When a spreadsheet won't cut the mustard
Winchester 2	Running PostgreSQL in Hybrid Data Architectures			Materialized Views: Performance Shortcut or Operational Trap?			RDS Maintenance: Strategies for Patching and Version Upgrades						Defining success on your terms

	11: 00	11: 10	11: 20	11: 30	11: 40	11: 50	12: 00	12: 10	12: 20	12: 30	12: 40	12: 50	13: 00
Almaden Ballroom							Lunch
Almaden Foyer	Registration
San Pedro (Level C)	YMatrix mxvector: How to implement high performance pluggable vectorized executor in PostgreSQL			Debezium and PostgreSQL in Action									The Open Source Approach: Building Production-Ready AI Apps with Postgres
Santa Clara (Level C)	A benchmark study on the impact of PostgreSQL server parameter tuning												We are all the 99th percentile
Winchester	When a spreadsheet won't cut the mustard			Vector Database Performance Challenges, A CaseStudy									What Can An AI Assistant Do For You?
Winchester 2	Defining success on your terms

	13: 00	13: 10	13: 20	13: 30	13: 40	13: 50	14: 00	14: 10	14: 20	14: 30	14: 40	14: 50	15: 00
Almaden Ballroom
Almaden Foyer	Registration
San Pedro (Level C)	The Open Source Approach: Building Production-Ready AI Apps with Postgres						From Transactions to Agents: PostgreSQL in Modern AI Applications			Building Durable Programs with Postgres			Building Agentic AI Applications with PostgreSQL as the Backbone
Santa Clara (Level C)	We are all the 99th percentile			YMatrix Domino: Design Considerations, Trade-offs, and Implementation of In-Database Stream Processing			The Elephant in the Room: Tackling PostgreSQL Major Version Upgrades Head-On						Enhancing PostgreSQL Sharding Through Agentic AI: Scalability, Optimization, and Autonomous Management
Winchester	What Can An AI Assistant Do For You?						PostgreSQL 18: The Evolution Continues — What’s New This Year						Mastering PostgreSQL Partitioning: Advanced Questions and Demos
Winchester 2

	15: 00	15: 10	15: 20	15: 30	15: 40	15: 50	16: 00	16: 10	16: 20	16: 30	16: 40	16: 50	17: 00
Almaden Ballroom
Almaden Foyer	Registration
San Pedro (Level C)	Building Agentic AI Applications with PostgreSQL as the Backbone						Beyond Text: Building Multimodal Search with pgvector in PostgreSQL
Santa Clara (Level C)	Enhancing PostgreSQL Sharding Through Agentic AI: Scalability, Optimization, and Autonomous Management						Migrating Oracle RAC to PostgreSQL Using Ora2Pg
Winchester	Mastering PostgreSQL Partitioning: Advanced Questions and Demos						Intel® AVX-512 Accelerates PostgreSQL 18 CRC32C Checksums
Winchester 2

	17: 00	17: 10	17: 20	17: 30	17: 40	17: 50	18: 00	18: 10	18: 20	18: 30	18: 40	18: 50	19: 00
Almaden Ballroom
Almaden Foyer
San Pedro (Level C)
Santa Clara (Level C)
Winchester
Winchester 2

	19: 00	19: 10	19: 20	19: 30	19: 40	19: 50	20: 00	20: 10	20: 20	20: 30	20: 40	20: 50	21: 00
Almaden Ballroom
Almaden Foyer
San Pedro (Level C)
Santa Clara (Level C)
Winchester
Winchester 2

	07: 00	07: 10	07: 20	07: 30	07: 40	07: 50	08: 00	08: 10	08: 20	08: 30	08: 40	08: 50	09: 00	09: 10	09: 20	09: 30	09: 40	09: 50	10: 00
Almaden Ballroom
Almaden Foyer										Registration
San Pedro (Level C)													Building Real-Time, Data-Aware Intelligence with Postgres & Model Context Protocol (MCP)						Using Postgres to locate the best coffee near you! ☕
Santa Clara (Level C)													Autonomous PostgreSQL: When AI Agents Become Your DBA						Elevate your DBA toolset with pg collector
Winchester													The power of mentorship						Implementing Transparent Data Encryption At Rest
Winchester 2													Running PostgreSQL in Hybrid Data Architectures			Materialized Views: Performance Shortcut or Operational Trap?			RDS Maintenance: Strategies for Patching and Version Upgrades

	10: 00	10: 10	10: 20	10: 30	10: 40	10: 50	11: 00	11: 10	11: 20	11: 30	11: 40	11: 50	12: 00	12: 10	12: 20	12: 30	12: 40	12: 50	13: 00
Almaden Ballroom													Lunch
Almaden Foyer	Registration
San Pedro (Level C)	Using Postgres to locate the best coffee near you! ☕						YMatrix mxvector: How to implement high performance pluggable vectorized executor in PostgreSQL			Debezium and PostgreSQL in Action									The Open Source Approach: Building Production-Ready AI Apps with Postgres
Santa Clara (Level C)	Elevate your DBA toolset with pg collector						A benchmark study on the impact of PostgreSQL server parameter tuning												We are all the 99th percentile
Winchester	Implementing Transparent Data Encryption At Rest						When a spreadsheet won't cut the mustard			Vector Database Performance Challenges, A CaseStudy									What Can An AI Assistant Do For You?
Winchester 2	RDS Maintenance: Strategies for Patching and Version Upgrades						Defining success on your terms

	13: 00	13: 10	13: 20	13: 30	13: 40	13: 50	14: 00	14: 10	14: 20	14: 30	14: 40	14: 50	15: 00	15: 10	15: 20	15: 30	15: 40	15: 50	16: 00
Almaden Ballroom
Almaden Foyer	Registration
San Pedro (Level C)	The Open Source Approach: Building Production-Ready AI Apps with Postgres						From Transactions to Agents: PostgreSQL in Modern AI Applications			Building Durable Programs with Postgres			Building Agentic AI Applications with PostgreSQL as the Backbone						Beyond Text: Building Multimodal Search with pgvector in PostgreSQL
Santa Clara (Level C)	We are all the 99th percentile			YMatrix Domino: Design Considerations, Trade-offs, and Implementation of In-Database Stream Processing			The Elephant in the Room: Tackling PostgreSQL Major Version Upgrades Head-On						Enhancing PostgreSQL Sharding Through Agentic AI: Scalability, Optimization, and Autonomous Management						Migrating Oracle RAC to PostgreSQL Using Ora2Pg
Winchester	What Can An AI Assistant Do For You?						PostgreSQL 18: The Evolution Continues — What’s New This Year						Mastering PostgreSQL Partitioning: Advanced Questions and Demos						Intel® AVX-512 Accelerates PostgreSQL 18 CRC32C Checksums
Winchester 2

	16: 00	16: 10	16: 20	16: 30	16: 40	16: 50	17: 00	17: 10	17: 20	17: 30	17: 40	17: 50	18: 00	18: 10	18: 20	18: 30	18: 40	18: 50	19: 00
Almaden Ballroom
Almaden Foyer
San Pedro (Level C)	Beyond Text: Building Multimodal Search with pgvector in PostgreSQL
Santa Clara (Level C)	Migrating Oracle RAC to PostgreSQL Using Ora2Pg
Winchester	Intel® AVX-512 Accelerates PostgreSQL 18 CRC32C Checksums
Winchester 2

	19: 00	19: 10	19: 20	19: 30	19: 40	19: 50	20: 00	20: 10	20: 20	20: 30	20: 40	20: 50	21: 00	21: 10	21: 20	21: 30	21: 40	21: 50	22: 00
Almaden Ballroom
Almaden Foyer
San Pedro (Level C)
Santa Clara (Level C)
Winchester
Winchester 2

	07: 00	07: 10	07: 20	07: 30	07: 40	07: 50	08: 00
Almaden Ballroom
Almaden Foyer
San Pedro (Level C)
Santa Clara (Level C)
Winchester

	08: 00	08: 10	08: 20	08: 30	08: 40	08: 50	09: 00
Almaden Ballroom
Almaden Foyer				Registration
San Pedro (Level C)
Santa Clara (Level C)
Winchester

	09: 00	09: 10	09: 20	09: 30	09: 40	09: 50	10: 00
Almaden Ballroom					Serious Beesness: Life Lessons from the Hive		When Trust Becomes Infrastructure: Secure-by-Default Postgres for the AI Era
Almaden Foyer	Registration
San Pedro (Level C)
Santa Clara (Level C)
Winchester

	10: 00	10: 10	10: 20	10: 30	10: 40	10: 50	11: 00
Almaden Ballroom	When Trust Becomes Infrastructure: Secure-by-Default Postgres for the AI Era		Postgres @ Amazon
Almaden Foyer	Registration
San Pedro (Level C)
Santa Clara (Level C)
Winchester

	11: 00	11: 10	11: 20	11: 30	11: 40	11: 50	12: 00
Almaden Ballroom			How I took my open source business to a Fortune 500 company		The Power of the Pause		Lunch
Almaden Foyer	Registration
San Pedro (Level C)
Santa Clara (Level C)
Winchester

	12: 00	12: 10	12: 20	12: 30	12: 40	12: 50	13: 00
Almaden Ballroom	Lunch						Running PostgreSQL in Kubernetes with CloudNativePG
Almaden Foyer	Registration
San Pedro (Level C)							Beyond vectors: Postgres for Production AI Agents
Santa Clara (Level C)							Logging with Purpose: A Framework for Finding and Fixing Slow Queries in Postgres
Winchester							Stop Guessing: How to Actually Fix PostgreSQL Performance

	13: 00	13: 10	13: 20	13: 30	13: 40	13: 50	14: 00
Almaden Ballroom	Running PostgreSQL in Kubernetes with CloudNativePG
Almaden Foyer	Registration
San Pedro (Level C)	Beyond vectors: Postgres for Production AI Agents						Replacing Oracle’s Advanced Features in PostgreSQL: High Availability, Advanced Functions, and Extensibility
Santa Clara (Level C)	Logging with Purpose: A Framework for Finding and Fixing Slow Queries in Postgres						Rewiring for Resilience
Winchester	Stop Guessing: How to Actually Fix PostgreSQL Performance						Model Your Data Before You Move it

	14: 00	14: 10	14: 20	14: 30	14: 40	14: 50	15: 00
Almaden Ballroom	Running PostgreSQL in Kubernetes with CloudNativePG
Almaden Foyer	Registration
San Pedro (Level C)	Replacing Oracle’s Advanced Features in PostgreSQL: High Availability, Advanced Functions, and Extensibility						Hybrid Search in PostgreSQL: Combining Vector and Full-Text for Real-World Applications
Santa Clara (Level C)	Rewiring for Resilience						Building Multi Master Workflows on PostgreSQL Logical Replication
Winchester	Model Your Data Before You Move it						Parallel query is silently stealing your CPU

	15: 00	15: 10	15: 20	15: 30	15: 40	15: 50	16: 00
Almaden Ballroom	Running PostgreSQL in Kubernetes with CloudNativePG
Almaden Foyer	Registration
San Pedro (Level C)	Hybrid Search in PostgreSQL: Combining Vector and Full-Text for Real-World Applications						Solar Power in the Pacific NW
Santa Clara (Level C)	Building Multi Master Workflows on PostgreSQL Logical Replication						PostgreSQL I/O Mechanisms Performance Comparison
Winchester	Parallel query is silently stealing your CPU						PostgreSQL Housekeeping: The Complete VACUUM Handbook

	16: 00	16: 10	16: 20	16: 30	16: 40	16: 50	17: 00
Almaden Ballroom
Almaden Foyer
San Pedro (Level C)	Solar Power in the Pacific NW			Schema-First PostgreSQL Migrations Without a DSL
Santa Clara (Level C)	PostgreSQL I/O Mechanisms Performance Comparison
Winchester	PostgreSQL Housekeeping: The Complete VACUUM Handbook

	17: 00	17: 10	17: 20	17: 30	17: 40	17: 50	18: 00
Almaden Ballroom
Almaden Foyer
San Pedro (Level C)
Santa Clara (Level C)
Winchester

	18: 00	18: 10	18: 20	18: 30	18: 40	18: 50	19: 00
Almaden Ballroom
Almaden Foyer
San Pedro (Level C)
Santa Clara (Level C)
Winchester

	19: 00	19: 10	19: 20	19: 30	19: 40	19: 50	20: 00
Almaden Ballroom
Almaden Foyer
San Pedro (Level C)
Santa Clara (Level C)
Winchester

	07: 00	07: 10	07: 20	07: 30	07: 40	07: 50	08: 00	08: 10	08: 20	08: 30	08: 40	08: 50	09: 00
Almaden Ballroom
Almaden Foyer										Registration
San Pedro (Level C)
Santa Clara (Level C)
Winchester

	09: 00	09: 10	09: 20	09: 30	09: 40	09: 50	10: 00	10: 10	10: 20	10: 30	10: 40	10: 50	11: 00
Almaden Ballroom					Serious Beesness: Life Lessons from the Hive		When Trust Becomes Infrastructure: Secure-by-Default Postgres for the AI Era		Postgres @ Amazon
Almaden Foyer	Registration
San Pedro (Level C)
Santa Clara (Level C)
Winchester

	11: 00	11: 10	11: 20	11: 30	11: 40	11: 50	12: 00	12: 10	12: 20	12: 30	12: 40	12: 50	13: 00
Almaden Ballroom			How I took my open source business to a Fortune 500 company		The Power of the Pause		Lunch						Running PostgreSQL in Kubernetes with CloudNativePG
Almaden Foyer	Registration
San Pedro (Level C)													Beyond vectors: Postgres for Production AI Agents
Santa Clara (Level C)													Logging with Purpose: A Framework for Finding and Fixing Slow Queries in Postgres
Winchester													Stop Guessing: How to Actually Fix PostgreSQL Performance

	13: 00	13: 10	13: 20	13: 30	13: 40	13: 50	14: 00	14: 10	14: 20	14: 30	14: 40	14: 50	15: 00
Almaden Ballroom	Running PostgreSQL in Kubernetes with CloudNativePG
Almaden Foyer	Registration
San Pedro (Level C)	Beyond vectors: Postgres for Production AI Agents						Replacing Oracle’s Advanced Features in PostgreSQL: High Availability, Advanced Functions, and Extensibility						Hybrid Search in PostgreSQL: Combining Vector and Full-Text for Real-World Applications
Santa Clara (Level C)	Logging with Purpose: A Framework for Finding and Fixing Slow Queries in Postgres						Rewiring for Resilience						Building Multi Master Workflows on PostgreSQL Logical Replication
Winchester	Stop Guessing: How to Actually Fix PostgreSQL Performance						Model Your Data Before You Move it						Parallel query is silently stealing your CPU

	15: 00	15: 10	15: 20	15: 30	15: 40	15: 50	16: 00	16: 10	16: 20	16: 30	16: 40	16: 50	17: 00
Almaden Ballroom	Running PostgreSQL in Kubernetes with CloudNativePG
Almaden Foyer	Registration
San Pedro (Level C)	Hybrid Search in PostgreSQL: Combining Vector and Full-Text for Real-World Applications						Solar Power in the Pacific NW			Schema-First PostgreSQL Migrations Without a DSL
Santa Clara (Level C)	Building Multi Master Workflows on PostgreSQL Logical Replication						PostgreSQL I/O Mechanisms Performance Comparison
Winchester	Parallel query is silently stealing your CPU						PostgreSQL Housekeeping: The Complete VACUUM Handbook

	17: 00	17: 10	17: 20	17: 30	17: 40	17: 50	18: 00	18: 10	18: 20	18: 30	18: 40	18: 50	19: 00
Almaden Ballroom
Almaden Foyer
San Pedro (Level C)
Santa Clara (Level C)
Winchester

	19: 00	19: 10	19: 20	19: 30	19: 40	19: 50	20: 00	20: 10	20: 20	20: 30	20: 40	20: 50	21: 00
Almaden Ballroom
Almaden Foyer
San Pedro (Level C)
Santa Clara (Level C)
Winchester

	07: 00	07: 10	07: 20	07: 30	07: 40	07: 50	08: 00	08: 10	08: 20	08: 30	08: 40	08: 50	09: 00	09: 10	09: 20	09: 30	09: 40	09: 50	10: 00
Almaden Ballroom																	Serious Beesness: Life Lessons from the Hive		When Trust Becomes Infrastructure: Secure-by-Default Postgres for the AI Era
Almaden Foyer										Registration
San Pedro (Level C)
Santa Clara (Level C)
Winchester

	10: 00	10: 10	10: 20	10: 30	10: 40	10: 50	11: 00	11: 10	11: 20	11: 30	11: 40	11: 50	12: 00	12: 10	12: 20	12: 30	12: 40	12: 50	13: 00
Almaden Ballroom	When Trust Becomes Infrastructure: Secure-by-Default Postgres for the AI Era		Postgres @ Amazon						How I took my open source business to a Fortune 500 company		The Power of the Pause		Lunch						Running PostgreSQL in Kubernetes with CloudNativePG
Almaden Foyer	Registration
San Pedro (Level C)																			Beyond vectors: Postgres for Production AI Agents
Santa Clara (Level C)																			Logging with Purpose: A Framework for Finding and Fixing Slow Queries in Postgres
Winchester																			Stop Guessing: How to Actually Fix PostgreSQL Performance

	13: 00	13: 10	13: 20	13: 30	13: 40	13: 50	14: 00	14: 10	14: 20	14: 30	14: 40	14: 50	15: 00	15: 10	15: 20	15: 30	15: 40	15: 50	16: 00
Almaden Ballroom	Running PostgreSQL in Kubernetes with CloudNativePG
Almaden Foyer	Registration
San Pedro (Level C)	Beyond vectors: Postgres for Production AI Agents						Replacing Oracle’s Advanced Features in PostgreSQL: High Availability, Advanced Functions, and Extensibility						Hybrid Search in PostgreSQL: Combining Vector and Full-Text for Real-World Applications						Solar Power in the Pacific NW
Santa Clara (Level C)	Logging with Purpose: A Framework for Finding and Fixing Slow Queries in Postgres						Rewiring for Resilience						Building Multi Master Workflows on PostgreSQL Logical Replication						PostgreSQL I/O Mechanisms Performance Comparison
Winchester	Stop Guessing: How to Actually Fix PostgreSQL Performance						Model Your Data Before You Move it						Parallel query is silently stealing your CPU						PostgreSQL Housekeeping: The Complete VACUUM Handbook

	16: 00	16: 10	16: 20	16: 30	16: 40	16: 50	17: 00	17: 10	17: 20	17: 30	17: 40	17: 50	18: 00	18: 10	18: 20	18: 30	18: 40	18: 50	19: 00
Almaden Ballroom
Almaden Foyer
San Pedro (Level C)	Solar Power in the Pacific NW			Schema-First PostgreSQL Migrations Without a DSL
Santa Clara (Level C)	PostgreSQL I/O Mechanisms Performance Comparison
Winchester	PostgreSQL Housekeeping: The Complete VACUUM Handbook

	19: 00	19: 10	19: 20	19: 30	19: 40	19: 50	20: 00	20: 10	20: 20	20: 30	20: 40	20: 50	21: 00	21: 10	21: 20	21: 30	21: 40	21: 50	22: 00
Almaden Ballroom
Almaden Foyer
San Pedro (Level C)
Santa Clara (Level C)
Winchester

	07: 00	07: 10	07: 20	07: 30	07: 40	07: 50	08: 00
Almaden Ballroom
Almaden Foyer
Patio (Outside Restaurant)
San Pedro (Level C)
Santa Clara (Level C)
Winchester

	08: 00	08: 10	08: 20	08: 30	08: 40	08: 50	09: 00
Almaden Ballroom
Almaden Foyer					Registration
Patio (Outside Restaurant)
San Pedro (Level C)							Technical Credibility Isn’t Enough: Communication Skills Every Senior Engineer Needs to Scale Impact
Santa Clara (Level C)							Demystifying PostgreSQL High Availability in the Cloud
Winchester							Postgres as a Control Plane: Design Patterns for Real-Time Compute Offload

	09: 00	09: 10	09: 20	09: 30	09: 40	09: 50	10: 00
Almaden Ballroom
Almaden Foyer	Registration
Patio (Outside Restaurant)
San Pedro (Level C)	Technical Credibility Isn’t Enough: Communication Skills Every Senior Engineer Needs to Scale Impact						“Autovacuum Blocked, Backlogged, or Slow?! Understanding Why It Can’t Keep Up”
Santa Clara (Level C)	Demystifying PostgreSQL High Availability in the Cloud						The Wellness OS
Winchester	Postgres as a Control Plane: Design Patterns for Real-Time Compute Offload						Modular Databases: We Put Postgres in package.json

	10: 00	10: 10	10: 20	10: 30	10: 40	10: 50	11: 00
Almaden Ballroom
Almaden Foyer	Registration
Patio (Outside Restaurant)
San Pedro (Level C)	“Autovacuum Blocked, Backlogged, or Slow?! Understanding Why It Can’t Keep Up”						Measuring shared_buffers Behavior on Large-Memory PostgreSQL Systems
Santa Clara (Level C)	The Wellness OS
Winchester	Modular Databases: We Put Postgres in package.json						Building an Efficient HTAP Architecture with PostgreSQL and Apache Doris with Native Doris Postgres CDC

	11: 00	11: 10	11: 20	11: 30	11: 40	11: 50	12: 00
Almaden Ballroom							Lunch
Almaden Foyer	Registration
Patio (Outside Restaurant)
San Pedro (Level C)	Measuring shared_buffers Behavior on Large-Memory PostgreSQL Systems
Santa Clara (Level C)	The Wellness OS				Don’t Standby, Stand-Up!
Winchester	Building an Efficient HTAP Architecture with PostgreSQL and Apache Doris with Native Doris Postgres CDC

	12: 00	12: 10	12: 20	12: 30	12: 40	12: 50	13: 00
Almaden Ballroom	Lunch
Almaden Foyer	Registration
Patio (Outside Restaurant)
San Pedro (Level C)							Narrating the Distributed Database on PostgreSQL journey
Santa Clara (Level C)							Autotuning PostgreSQL: A deep dive into server parameter tuning with agentic AI
Winchester							Let’s Build a Postgres Extension!

	13: 00	13: 10	13: 20	13: 30	13: 40	13: 50	14: 00
Almaden Ballroom
Almaden Foyer	Registration
Patio (Outside Restaurant)
San Pedro (Level C)	Narrating the Distributed Database on PostgreSQL journey						PostgreSQL Statistics Unleashed: Mastering Query Optimization Through Data-Driven Insights
Santa Clara (Level C)	Autotuning PostgreSQL: A deep dive into server parameter tuning with agentic AI						Accelerating PostgreSQL Backups with Intel® QuickAssist Technology
Winchester	Let’s Build a Postgres Extension!						Trust, But Verify: Operationalizing Data Consistency Checks for Postgres Logical Replication

	14: 00	14: 10	14: 20	14: 30	14: 40	14: 50	15: 00
Almaden Ballroom
Almaden Foyer	Registration
Patio (Outside Restaurant)
San Pedro (Level C)	PostgreSQL Statistics Unleashed: Mastering Query Optimization Through Data-Driven Insights			Leveraging Open-Source Data Platforms to Build Cost-Effective and Reliable Supply Chain Systems
Santa Clara (Level C)	Accelerating PostgreSQL Backups with Intel® QuickAssist Technology			Multigres: One stop PostgreSQL Management and Scaling
Winchester	Trust, But Verify: Operationalizing Data Consistency Checks for Postgres Logical Replication			DocumentDB on Postgres: Native BSON, Vectors, and Mongo Compatibility

	15: 00	15: 10	15: 20	15: 30	15: 40	15: 50	16: 00
Almaden Ballroom
Almaden Foyer	Registration
Patio (Outside Restaurant)
San Pedro (Level C)	Leveraging Open-Source Data Platforms to Build Cost-Effective and Reliable Supply Chain Systems			Manage Databases, Lead People
Santa Clara (Level C)	Multigres: One stop PostgreSQL Management and Scaling			Eight Steps to Bullet-Proof Database Disaster Recovery
Winchester	DocumentDB on Postgres: Native BSON, Vectors, and Mongo Compatibility			Rewriting the Postgres Engine

	16: 00	16: 10	16: 20	16: 30	16: 40	16: 50	17: 00
Almaden Ballroom
Almaden Foyer
Patio (Outside Restaurant)
San Pedro (Level C)	Manage Databases, Lead People			Safe PostgreSQL Migrations at Billion-Scale with Flyway
Santa Clara (Level C)	Eight Steps to Bullet-Proof Database Disaster Recovery			Past, Present, and Future: Logical Decoding and Replication in PostgreSQL
Winchester	Rewriting the Postgres Engine			Running Distributed PostgreSQL with Citus

	17: 00	17: 10	17: 20	17: 30	17: 40	17: 50	18: 00
Almaden Ballroom
Almaden Foyer
Patio (Outside Restaurant)
San Pedro (Level C)	Safe PostgreSQL Migrations at Billion-Scale with Flyway
Santa Clara (Level C)	Past, Present, and Future: Logical Decoding and Replication in PostgreSQL
Winchester	Running Distributed PostgreSQL with Citus

	18: 00	18: 10	18: 20	18: 30	18: 40	18: 50	19: 00
Almaden Ballroom
Almaden Foyer
Patio (Outside Restaurant)
San Pedro (Level C)
Santa Clara (Level C)
Winchester

	19: 00	19: 10	19: 20	19: 30	19: 40	19: 50	20: 00
Almaden Ballroom
Almaden Foyer
Patio (Outside Restaurant)
San Pedro (Level C)
Santa Clara (Level C)
Winchester

	07: 00	07: 10	07: 20	07: 30	07: 40	07: 50	08: 00	08: 10	08: 20	08: 30	08: 40	08: 50	09: 00
Almaden Ballroom
Almaden Foyer											Registration
Patio (Outside Restaurant)
San Pedro (Level C)													Technical Credibility Isn’t Enough: Communication Skills Every Senior Engineer Needs to Scale Impact
Santa Clara (Level C)													Demystifying PostgreSQL High Availability in the Cloud
Winchester													Postgres as a Control Plane: Design Patterns for Real-Time Compute Offload

	09: 00	09: 10	09: 20	09: 30	09: 40	09: 50	10: 00	10: 10	10: 20	10: 30	10: 40	10: 50	11: 00
Almaden Ballroom
Almaden Foyer	Registration
Patio (Outside Restaurant)
San Pedro (Level C)	Technical Credibility Isn’t Enough: Communication Skills Every Senior Engineer Needs to Scale Impact						“Autovacuum Blocked, Backlogged, or Slow?! Understanding Why It Can’t Keep Up”						Measuring shared_buffers Behavior on Large-Memory PostgreSQL Systems
Santa Clara (Level C)	Demystifying PostgreSQL High Availability in the Cloud						The Wellness OS
Winchester	Postgres as a Control Plane: Design Patterns for Real-Time Compute Offload						Modular Databases: We Put Postgres in package.json						Building an Efficient HTAP Architecture with PostgreSQL and Apache Doris with Native Doris Postgres CDC

	11: 00	11: 10	11: 20	11: 30	11: 40	11: 50	12: 00	12: 10	12: 20	12: 30	12: 40	12: 50	13: 00
Almaden Ballroom							Lunch
Almaden Foyer	Registration
Patio (Outside Restaurant)
San Pedro (Level C)	Measuring shared_buffers Behavior on Large-Memory PostgreSQL Systems												Narrating the Distributed Database on PostgreSQL journey
Santa Clara (Level C)	The Wellness OS				Don’t Standby, Stand-Up!								Autotuning PostgreSQL: A deep dive into server parameter tuning with agentic AI
Winchester	Building an Efficient HTAP Architecture with PostgreSQL and Apache Doris with Native Doris Postgres CDC												Let’s Build a Postgres Extension!

	13: 00	13: 10	13: 20	13: 30	13: 40	13: 50	14: 00	14: 10	14: 20	14: 30	14: 40	14: 50	15: 00
Almaden Ballroom
Almaden Foyer	Registration
Patio (Outside Restaurant)
San Pedro (Level C)	Narrating the Distributed Database on PostgreSQL journey						PostgreSQL Statistics Unleashed: Mastering Query Optimization Through Data-Driven Insights			Leveraging Open-Source Data Platforms to Build Cost-Effective and Reliable Supply Chain Systems
Santa Clara (Level C)	Autotuning PostgreSQL: A deep dive into server parameter tuning with agentic AI						Accelerating PostgreSQL Backups with Intel® QuickAssist Technology			Multigres: One stop PostgreSQL Management and Scaling
Winchester	Let’s Build a Postgres Extension!						Trust, But Verify: Operationalizing Data Consistency Checks for Postgres Logical Replication			DocumentDB on Postgres: Native BSON, Vectors, and Mongo Compatibility

	15: 00	15: 10	15: 20	15: 30	15: 40	15: 50	16: 00	16: 10	16: 20	16: 30	16: 40	16: 50	17: 00
Almaden Ballroom
Almaden Foyer	Registration
Patio (Outside Restaurant)
San Pedro (Level C)	Leveraging Open-Source Data Platforms to Build Cost-Effective and Reliable Supply Chain Systems			Manage Databases, Lead People						Safe PostgreSQL Migrations at Billion-Scale with Flyway
Santa Clara (Level C)	Multigres: One stop PostgreSQL Management and Scaling			Eight Steps to Bullet-Proof Database Disaster Recovery						Past, Present, and Future: Logical Decoding and Replication in PostgreSQL
Winchester	DocumentDB on Postgres: Native BSON, Vectors, and Mongo Compatibility			Rewriting the Postgres Engine						Running Distributed PostgreSQL with Citus

	17: 00	17: 10	17: 20	17: 30	17: 40	17: 50	18: 00	18: 10	18: 20	18: 30	18: 40	18: 50	19: 00
Almaden Ballroom
Almaden Foyer
Patio (Outside Restaurant)
San Pedro (Level C)	Safe PostgreSQL Migrations at Billion-Scale with Flyway
Santa Clara (Level C)	Past, Present, and Future: Logical Decoding and Replication in PostgreSQL
Winchester	Running Distributed PostgreSQL with Citus

	19: 00	19: 10	19: 20	19: 30	19: 40	19: 50	20: 00	20: 10	20: 20	20: 30	20: 40	20: 50	21: 00
Almaden Ballroom
Almaden Foyer
Patio (Outside Restaurant)
San Pedro (Level C)
Santa Clara (Level C)
Winchester

	07: 00	07: 10	07: 20	07: 30	07: 40	07: 50	08: 00	08: 10	08: 20	08: 30	08: 40	08: 50	09: 00	09: 10	09: 20	09: 30	09: 40	09: 50	10: 00
Almaden Ballroom
Almaden Foyer											Registration
Patio (Outside Restaurant)
San Pedro (Level C)													Technical Credibility Isn’t Enough: Communication Skills Every Senior Engineer Needs to Scale Impact						“Autovacuum Blocked, Backlogged, or Slow?! Understanding Why It Can’t Keep Up”
Santa Clara (Level C)													Demystifying PostgreSQL High Availability in the Cloud						The Wellness OS
Winchester													Postgres as a Control Plane: Design Patterns for Real-Time Compute Offload						Modular Databases: We Put Postgres in package.json

	10: 00	10: 10	10: 20	10: 30	10: 40	10: 50	11: 00	11: 10	11: 20	11: 30	11: 40	11: 50	12: 00	12: 10	12: 20	12: 30	12: 40	12: 50	13: 00
Almaden Ballroom													Lunch
Almaden Foyer	Registration
Patio (Outside Restaurant)
San Pedro (Level C)	“Autovacuum Blocked, Backlogged, or Slow?! Understanding Why It Can’t Keep Up”						Measuring shared_buffers Behavior on Large-Memory PostgreSQL Systems												Narrating the Distributed Database on PostgreSQL journey
Santa Clara (Level C)	The Wellness OS										Don’t Standby, Stand-Up!								Autotuning PostgreSQL: A deep dive into server parameter tuning with agentic AI
Winchester	Modular Databases: We Put Postgres in package.json						Building an Efficient HTAP Architecture with PostgreSQL and Apache Doris with Native Doris Postgres CDC												Let’s Build a Postgres Extension!

	13: 00	13: 10	13: 20	13: 30	13: 40	13: 50	14: 00	14: 10	14: 20	14: 30	14: 40	14: 50	15: 00	15: 10	15: 20	15: 30	15: 40	15: 50	16: 00
Almaden Ballroom
Almaden Foyer	Registration
Patio (Outside Restaurant)
San Pedro (Level C)	Narrating the Distributed Database on PostgreSQL journey						PostgreSQL Statistics Unleashed: Mastering Query Optimization Through Data-Driven Insights			Leveraging Open-Source Data Platforms to Build Cost-Effective and Reliable Supply Chain Systems						Manage Databases, Lead People
Santa Clara (Level C)	Autotuning PostgreSQL: A deep dive into server parameter tuning with agentic AI						Accelerating PostgreSQL Backups with Intel® QuickAssist Technology			Multigres: One stop PostgreSQL Management and Scaling						Eight Steps to Bullet-Proof Database Disaster Recovery
Winchester	Let’s Build a Postgres Extension!						Trust, But Verify: Operationalizing Data Consistency Checks for Postgres Logical Replication			DocumentDB on Postgres: Native BSON, Vectors, and Mongo Compatibility						Rewriting the Postgres Engine

	16: 00	16: 10	16: 20	16: 30	16: 40	16: 50	17: 00	17: 10	17: 20	17: 30	17: 40	17: 50	18: 00	18: 10	18: 20	18: 30	18: 40	18: 50	19: 00
Almaden Ballroom
Almaden Foyer
Patio (Outside Restaurant)
San Pedro (Level C)	Manage Databases, Lead People			Safe PostgreSQL Migrations at Billion-Scale with Flyway
Santa Clara (Level C)	Eight Steps to Bullet-Proof Database Disaster Recovery			Past, Present, and Future: Logical Decoding and Replication in PostgreSQL
Winchester	Rewriting the Postgres Engine			Running Distributed PostgreSQL with Citus

	19: 00	19: 10	19: 20	19: 30	19: 40	19: 50	20: 00	20: 10	20: 20	20: 30	20: 40	20: 50	21: 00	21: 10	21: 20	21: 30	21: 40	21: 50	22: 00
Almaden Ballroom
Almaden Foyer
Patio (Outside Restaurant)
San Pedro (Level C)
Santa Clara (Level C)
Winchester

Privacy Statement

Privacy Statement

PGCentral Foundation, its agents, subsidiaries and affiliates (“PGFoundation”) produces the Postgres Conference Series (collectively, the “Events”), and is committed to respecting your privacy. By using or accessing our products, services or Site (defined below) in any manner, you agree to this Privacy Statement and the website Terms of Use. If you do not agree to be bound by these terms, please leave the Site.

As we continually work to improve our Services (defined below), we may need to change this Privacy Policy from time to time. Upon such changes, we will alert you to any such changes by placing a notice on the Postgres Conference Site, by sending you an email and/or by some other means. Please note that if you’ve opted not to receive legal notice emails from us (or you haven’t provided us with your email address), those legal notices will still govern your use of the Services. You are still responsible for reading and understanding them. If you use the Services after any changes to the Privacy Policy have been posted, that means you agree to all of the changes.

Definitions: “Personal Data” means any information relating to an identified or identifiable natural person and any other data or information that constitutes personal data or personal information under any applicable Data Protection Law. Without limiting the foregoing, an identifiable natural person is one who can be identified, directly or indirectly, in particular by referencing (i) an identifier such as a person’s name, e-mail address, phone number, account numbers, government-issued ID numbers, or an online identifier; (ii) location data such as an IP address, (iii) financial information, (iv) one or more factors specific to the physical, physiological, genetic, mental, economic, cultural, or social identity of that natural person, or (v) information associated or combined with Personal Data. “Controller” means the natural or legal person, agency, or other body which alone or jointly with others determines the purposes and means of the processing of Personal Data; where the purposes and means of processing are determined by the European Union or Member State laws, the controller (or the criteria for nominating the controller) may be designated by those laws. “Data Protection Law” means any law, rule, regulation, decree, statute, or other enactment, order, mandate or resolution, applicable to Event Organizer or Sponsors, relating to data security, anti-spam, data protection and/or privacy, including Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to processing of personal data and the free movement of that data (“GDPR”), the California Consumer Privacy Act (“CCPA”), and any implementing, derivative or related legislation, rule, regulation, and regulatory guidance, as amended, extended, repealed and replaced, or re-enacted.

General Statement: Personal Data is collected for all attendees for registration and promotion purposes. We do not release or sell attendee data. All associated parties will comply with Data Protection Law, any applicable anti-spam legislation and will protect Personal Data from unauthorized use, access or disclosure.

If Personal Data is given out, it is done at the will of the attendee during the event via lead scanning or card drops.

In addition, if either the Event Organizer or Sponsors intend to share Personal Data of Event attendees or visitors with one another at the direction of the applicable Event attendees or visitors, the parties agree that each will be independently responsible for complying with the obligations under Data Protection Law (e.g., independent Controllers under GDPR or the equivalent concept under CCPA). These obligations include, without limitation, providing appropriate notice to and obtaining consent from Event attendees and visitors to share their Personal Data with the other party, and for the party receiving it to use Personal Data for the purposes of contacting individuals about the receiving party’s products, services, events, or offers.

In the event that either party shares Personal Data at the direction of the other party and not at the direction of the attendees/visitors, (i) the parties will use the Personal Data only in connection with their direct business relationship and (ii) neither party will transfer or sell the Personal Data to any third party except to contractually bound sub-processors operating on behalf of that party. Both parties hereby certify that they understand the above restrictions and will comply with them.

Presentation Guidelines

Presentation Guidelines

Why Guidelines

The Postgres Conference is a non-profit, community driven conference series delivering the largest education and advocacy platform for Postgres. In an effort to create a productive and profitable environment for our community we must set a bar of expectation for content and we set the bar high.

The community is comprised of users, developers, core-contributors, sponsors, advocates, and external communities. We work hard to create a professional, valuable, and highly educational environment that produces a net result of, “Wow, that conference was very well done. It had great content with knowledgeable professionals, educators and advocates!”

Types of Presentations We Accept

Any presentation that has a tie-in to Postgres will be considered for acceptance into one of our event programs. This includes, but is not limited to, presentations on Open Source Projects, Postgres forks, extensions, new APIs, and languages. As a conference that makes it a goal to incorporate the entire community we also consider business cases, product talks, and service presentations. Presentations that are not related to the success of Postgres will not be considered.

Laptop connections supported

The Postgres Conference will provide a HDMI connection. If you do not have a HDMI port, it is the speaker’s responsibility to provide an adapter.

What about X technology?

When considering whether to submit a topic or not, ask yourself, “Is this presentation in some way related to the success of Postgres?” If it is, then it will be considered. This includes limitations of our great database. It also includes forks of Postgres both closed and Open Source. These types projects and products ultimately contribute to the success of Postgres.

How do presentations on forks or closed source versions help the success of Postgres?

Postgres is BSD style licensed. The BSD license is a true freedom license. The only license that maintains a higher level of freedom for Open Source development is the anti-license: Public Domain. That means the community embraces all forms of use for Postgres as long as it abides by the license.

A presentation on RDS Postgres, Google Cloud Postgres or Greenplum increases overall success via visibility, lowers the barrier of entry for new Postgres users, and supports our commercial community with hard earned efforts to create Postgres products.

Shouldn’t the community be promoting Open Source solutions over proprietary closed source solutions?

Yes, the end goal is that the deployed Postgres is the Open Source Postgres and preference will always be given to Open Source Postgres presentations. However, we offer presentation opportunities to our sponsors that may or may not advocate Open Source Postgres. Sponsors are welcome to present on any topic as long as it follows the guideline of: Does it promote the success of Postgres?

Types of Presentations

PostgresConf offers several presentation opportunities:

Presentation: 20 minutes
Breakout Sessions: 50 minutes
Keynotes: 10 and 20 minutes
Half and Full Day trainings (NOTE: Paid registrants receive priority seating, and trainings are restricted according to badge level)

Code of Conduct

Code of Conduct

Introduction

Postgres Conference (PostgresConf) prides itself on the quality of our community and our work, and the technical and professional accomplishments of our community. We expect everyone who participates to conduct themselves in a professional manner, acting with common courtesy and in the common interest, with respect for all of our community.

It is the expectation that PostgresConf community members will adhere to the PostgresConf Code of Conduct (CoC).

Inclusivity and Appropriate Conduct

PostgresConf is open to participation by anyone with an interest in working with Postgres and related technologies, regardless of their level of experience with the software, or with technology in general. We encourage contributions from all individuals, whatever their background may be.

Personal attacks and negative comments on personal characteristics are unacceptable, and will not be permitted. Examples of personal characteristics include, but are not limited to age, race, national origin or ancestry, religion, political affiliation, gender, or sexual orientation.

Additional behaviors which are also violations of this CoC include, but are not limited to, threats of violence against an individual or group, threats of professional, community, and/or project sabotage, unwelcome sexual attention in any form, engaging in behavior that may bring PostgresConf into disrepute, and refusing to cease inappropriate conduct when requested to do so.

Retaliation

It is also expressly forbidden for anyone to retaliate against a person who brings a complaint under this CoC, or who assists in investigating such a complaint. Retaliation may take the form of, among other actions: further personal attacks (public or private); actions which undermine an individual's professional status and/or status with their employer, coworkers, clients, or community; actions which threaten the individual's privacy, physical person, well-being, home, and/or family. Acts of retaliation will be treated in the same manner as any other violation of this CoC.

Reporting

PostgresConf believes that only objective parties can properly handle Code of Conduct issues. Therefore we contract with Lighthouse an independent and objective party to handle all reports.

There are three ways to submit a report 24 hours a day:

Website: https://www.lighthouse-services.com/postgresconf
Toll-Free Telephone:
English speaking USA and Canada: 833-490-0007
Spanish speaking USA and Canada: 800-216-1288
E-mail: reports@lighthouse-services.com (include PG Central Foundation within the report)

Acting in Good Faith

Any allegations that prove not to be substantiated, and which prove to have been made maliciously or knowingly to be false, will be viewed as a serious community offense and a violation of this CoC.

Conclusion

We encourage appropriate and collegial relationships among community members; however, members must be sensitive to conduct that may be considered offensive by fellow members and must refrain from engaging in such conduct.

In all interactions with the community, use your professional judgment, and keep the discussion focused on moving our project and our community forward in a positive direction for all.

This tool is free software, released under the MIT license. You can run, copy, distribute, study, change and improve it. The source code and the developers are on github.