That’s a fair question!
A concrete case where this comes up is multi-omics research. A single study routinely combines ~20k gene expression values, 100k–1M SNPs, thousands of proteins and metabolites, plus clinical metadata — all per patient.
Today, this data is almost never stored in relational tables. It lives in files and in-memory matrices, and a large part of the work is repeatedly rebuilding wide matrices just to explore subsets of features or cohorts.
In that context, a “wide table” isn’t about transactions or joins — it’s about having a persistent, queryable representation of a matrix that already exists conceptually. Integration becomes “load patients”, and exploration becomes SELECT statements.
I’m not claiming this fits every workload, but based on how much time is currently spent on data reshaping in multi-omics, I’m confident there is a real need for this kind of model.
A concrete case where this comes up is multi-omics research. A single study routinely combines ~20k gene expression values, 100k–1M SNPs, thousands of proteins and metabolites, plus clinical metadata — all per patient.
Today, this data is almost never stored in relational tables. It lives in files and in-memory matrices, and a large part of the work is repeatedly rebuilding wide matrices just to explore subsets of features or cohorts.
In that context, a “wide table” isn’t about transactions or joins — it’s about having a persistent, queryable representation of a matrix that already exists conceptually. Integration becomes “load patients”, and exploration becomes SELECT statements.
I’m not claiming this fits every workload, but based on how much time is currently spent on data reshaping in multi-omics, I’m confident there is a real need for this kind of model.