Postgres on NVMe: performance and the convergence of transactions and analytics

PostgreSQL performance issues at large scale often stem from storage latency once the working set exceeds memory, affecting ingestion, read consistency, VACUUM, checkpoints, and logical replication. A benchmark using a 482 GiB pgbench dataset found that local NVMe storage delivered 9.2 times the throughput of baseline gp3 EBS, with median update latency falling from 36.9 ms to 4.0 ms, largely because EBS-backed processes spent most of their time waiting for data reads. Although local NVMe is ephemeral, the proposed design combines synchronous quorum replication across availability zones with continuous WAL archival to provide resilience, recovery, and point-in-time restore capabilities. The discussion also argues that faster disks improve transactional PostgreSQL workloads but cannot make its row-oriented layout efficient for large analytical scans, for which a columnar system such as ClickHouse is more suitable. It recommends retaining PostgreSQL for ACID transactions and point lookups while using WAL-based change data capture, query pushdown, and schema synchronization to replicate data to ClickHouse for near-real-time analytics, including a newer physical-WAL-based WalShadow option intended to enable sub-second replication.

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