Schema-on-read is the defining trade. Because structure is imposed at query time, the lake accepts anything — logs, images, JSON events, sensor streams — without deciding its future use in advance. The flexibility is real for exploration and ML training corpora, and so is the deferred cost: every consumer must interpret the data, and nobody validated it on the way in.
The failure mode has a name: the data swamp. Without a catalog, ownership and retention policy, a lake fills with files nobody can find, trust or delete, and cheap storage becomes expensive indecision. The controls are known and must exist from day one — a catalog that makes data discoverable, an owner per dataset, documented schemas where they exist, and lifecycle rules that expire what is no longer needed.
The warehouse/lake boundary has largely dissolved into the lakehouse pattern. Open table formats — Delta Lake, Apache Iceberg — bring ACID transactions, schema enforcement and time travel to data on object storage, so one platform can serve BI and ML from the same files. The practical decision is no longer lake versus warehouse but which table format and query engines fit your workloads, with governance as the layer that decides whether the whole thing is an asset or a liability.
Lakes that work are organised in zones of increasing trust: a raw landing zone kept immutable, a cleaned and validated zone where schema is enforced, and a curated zone shaped for consumption. The discipline mirrors warehouse layering, and it is what keeps schema-on-read honest — flexibility at the edge, rigour where decisions are made. A lake without zones is a swamp with a roadmap.
A lake is also the wrong choice more often than vendors suggest. A team whose data is structured, whose questions are analytical and whose scale is modest gets more from a warehouse with far less governance overhead. The lake earns its complexity with machine-learning training corpora, high-volume telemetry, media and documents — workloads whose shape is not known at write time and whose volume makes warehouse pricing sting. Choosing one because it sounds like the future is how swamps get founded.
Codazz builds this in production — AI & ML Development.