Glowing data pathways weave through a multi-level logistics hub filled with servers and operators.
Pip: If you have ever looked at your organisation’s data landscape and thought “this resembles a motorway junction designed by someone who hates drivers,” then Martyn Jones has a blueprint with your name on it.
Mara: This episode follows a series of posts introducing the Data Logistics Hub — covering what the concept is, why the pain points are real, how strategy and architecture hold it together, and what the actual components look like in practice.
Pip: Let’s start with the foundations — what the hub is and why it exists.
Martyn Rhisiart Jones, Madrid, Friday 27th March 2026
Warehousing Your Data: A No-Nonsense Guide to the Right DBMS in 2026
Listen, you glorious data martyrs. You noble sufferers who have spent far too many evenings coaxing historical rows into slowly changing dimension tables while the rest of the office has gone home to sensible lives. You know the drill. The star schema looks perfect on paper, the fact table is append-only and cooperative, but then someone asks for last year’s corrected customer segments. Suddenly, your backfill script is performing open-heart surgery on a live production warehouse.
In 2026, vendors are still shouting about infinite scalability and “agentic AI” (whatever that means this week), but what actually matters is a system that lets you shove yesterday’s data into those dimension objects without it feeling like a hostage negotiation.
I have been asked to examine the most appropriate database management systems for effective data warehousing, with particular attention to the pain of backfilling dimensional tables. The brief is clear: functionality, reliability, scalability, extensibility, maintainability, performance, cost, ease of use, and a total lack of corporate nonsense.
