# Alexander Ioffe: Why is my Whale Query 1000x Slower in Prod? Databases hate skew, each hates it differently

> **Key Architectural Takeaway:** Ten enterprise customers own 80% of the orders.

**Published:** 2026-10-13T00:00:00+00:00  
**Source:** Planet PostgreSQL  
**Category:** databases-storage  
**Canonical URL:** https://fosswire.org/news/alexander-ioffe-why-is-my-whale-query-1000x-slower-in-prod-d.html  

## Executive Summary
Ten enterprise customers own 80% of the orders. On uniform test data the query runs in ~1ms; on that real skew it runs ~1,000x slower. The fix doesn't transfer between engines: Postgres is rescued by one free session setting, SQL Server can't be touched by it and needs a completely different access-path fix. Measured on Neon and Azure SQL Database using ExoBench.

## Architectural & Systems Analysis
From an OLTP/OLAP systems architecture, storage tiering, and data durability perspective:

- **Zero-Vendor Lock-in Formats:** Leveraging open specifications (e.g. Parquet, Iceberg) ensures multi-engine interoperability without ingestion lock-in.
- **Vector & In-Memory Throughput:** Modern memory layouts and SIMD-accelerated execution pipelines minimize latency in real-time retrieval.
- **Distributed Resiliency:** Decoupled storage and compute layers enable elastic horizontal scaling with strict ACID guarantees.

## Impact on the Open Ecosystem
Empowers data engineers with open, self-hosted alternatives to monopolistic cloud database providers.