Database Technology

ClickHouse released WalShadow, a tool that replicates PostgreSQL data by reading the physical WAL stream rather than using logical decoding. It decodes heap records directly from the byte stream and writes them as ClickHouse-native blocks. This approach bypasses standard logical replication mechanisms to achieve data synchronization.

• Bypasses logical decoding overhead by reading raw physical WAL bytes
• Decodes heap records internally to generate ClickHouse-native block formats
• Offers an alternative replication path for Postgres to ClickHouse workflows
• Requires careful monitoring as it operates outside standard logical replication

Chris van Eijk outlines six critical choices for building multi-tenant SaaS on PostgreSQL, covering isolation models, Row Level Security, indexing strategies, monetary data types, tenant restoration, and large-scale migration. The analysis provides measured comparisons to help engineers select the right architecture for their specific scale and compliance needs. It emphasizes practical trade-offs rather than theoretical best practices.

• Choose isolation models based on strict compliance vs. resource efficiency trade-offs.
• Implement RLS carefully to balance security overhead with query performance.
• Select indexing strategies that support multi-tenant filtering without bloat.
• Use appropriate money types to avoid precision issues in financial data.
• Plan restoration and migration paths early to minimize tenant downtime.

Chris van Eijk analyzes how Row-Level Security, though easy to enable, often fails silently in PostgreSQL 17. The article details five specific scenarios where tenant data leaks despite configuration, highlighting edge cases in policy enforcement. This review serves as a practical audit guide for ensuring strict multi-tenancy isolation.

• Enabling RLS is trivial, but verifying its persistence against policy changes is critical.
• Five distinct leak paths exist where tenant boundaries are silently breached in v17.
• Audit existing policies for edge cases that bypass row-level filtering mechanisms.
• Assume RLS is broken until specific edge-case scenarios are explicitly tested.

Dimitri Fontaine reflects on the decade since Postgres 10 introduced logical replication, contrasting it with the complex, multi-daemon setups of Londiste and PgQ. He notes that every release since 2017 has replaced manual plumbing with declarative SQL, simplifying data distribution. This article launches a series exploring modern use-cases and the evolution of the feature set.

• Logical replication has replaced complex trigger-based queues like PgQ and Londiste with native SQL commands.
• Postgres 19 marks the 10th anniversary of this feature, highlighting a decade of incremental stabilization.
• The shift reduces operational overhead by eliminating Python daemons and per-node ticker processes.
• New series will cover practical use-cases now that the underlying plumbing is standardized.