When a production server encounters a sudden failure, the only thing standing between business continuity and catastrophic data loss is the write-ahead log. While the core philosophy is universal-write sequentially to durable storage before touching data pages - the actual implementations across the major relational engines could not be more divergent.

​In this deep-dive architectural session, we pop the hood on MySQL’s dual-logging design (InnoDB Redo Log + Binary Log), PostgreSQL’s unified Write-Ahead Log (WAL), and SQL Server’s Transaction Log (LDF). We will inspect how raw records are structured on disk, trace a transaction's commit lifecycle across the engines, and analyze why their architectural choices directly dictate performance, CDC ingestion, and replication mechanics.

Key Takeaways / What Attendees Will Learn
- ​Architectural Trade-offs: Understand the difference between a unified physico-logical stream (Postgres WAL, SQL Server LDF) and a split-brain two-phase commit architecture (MySQL Redo + Binlog).
- ​Under the Microscope: Learn how raw records look across engines: from logical row events to physical page diffs and ARIES undo/redo byte vectors.
- ​Production Failure Modes: Identify and prevent critical disk exhaustion and latency bottlenecks caused by lagging replicas, unpurged slots, and VLF truncation blocks.
- ​CDC & Downstream Pipelines: Understand how CDC frameworks (e.g., Debezium, Kafka) consume these logs and the operational overhead associated with each engine's approach.

Every production database relies on an append-only log to survive crashes and stream changes, yet MySQL, PostgreSQL, and SQL Server approach this problem with radically different architectures. This session breaks down the internal mechanics of Binlogs, WAL, and LDF files, contrasting their write paths, durability trade-offs, and common production failure modes.