The Dynamic Duo? | Scaling Postgres 419

In this episode of Scaling Postgres, we discuss the dynamic duo of foreign tables and materialized views, the dangers of long-running transactions and job queues and why we cannot have transparent data encryption.

Content Discussed

• Foreign Tables and Materialized Views: A Dynamic Duo
• Long-running transactions, job queues, and the cascade that wreaks havoc
• Why Postgres Lacks Transparent Data Encryption
• Postgres as an Execution Environment for AI: Failure Modes, Hooks, and the ORBIT Framework
• pgvector 0.8.2 and the Trouble With Parallel HNSW
• How to hack Logical Replication in PostgreSQL: Insights from contributors
• Graph Queries Across Billions of Rows of Scattered Data with Postgres and Apache AGE™
• 5 PostgreSQL locking behaviors that trip people up
• What Else Is In There?
• TOAST: Where PostgreSQL hides big values
• On Polymorphic Associations in Postgres
• EXPLAIN Prettier, or Post-Processing Query Plans in Postgres
• A Correction: Snowflake Postgres Is Just Postgres
• Managed Postgres, Examined: Google AlloyDB for PostgreSQL
• The Postgres Developer's Guide to Vector Index Tradeoffs
• Automating PostgreSQL Index Tuning Using AI
• Critical PMM Alerts Every PostgreSQL DBA Must Track
• Understanding Why OS RAM and Postgres Buffer Cache Compete
• Scaling AI-Driven Marketing Processes with PostgreSQL
• REPACK CONCURRENTLY: pg_squeeze Gets a Promotion
• PGConf.dev 2026 Trip Summary
• PGConf.dev 2026: Why It Remains My Favorite PostgreSQL Conference
• My Reflections on PGConf.dev 2026
• The PostgreSQL Conference HOW2026 in Jinan, China
• Contributions for week 20, 2026
• How ApexAnalytica Runs Building Telemetry, Transactional Data, and RAG on a Single Postgres Instance
• Unify Your Plant-Floor Data with Claude Code and TimescaleDB
• How Neon's lakebase architecture stays resilient to cloud failures
• How a Multigres Cluster Bootstraps
• Drop-in Postgres, proven with a real app
• High availability from first principles
• The edge cases consensus protects you from
• Optimize costs in Amazon Aurora

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