Lakes, Warehouses & Lakehouses
Object storage, analytical warehouses, and the table-metadata layer that gave files transactions. Compared on data types, query patterns, governance, cost, openness and tooling — not on marketing.
One place to land structured, semi-structured and unstructured data before anyone knows which questions it will answer — and the reason most lakes become swamps.
An analytical database built for large scans and aggregations over structured, modelled data — and what it gives you that a pile of files cannot.
Object storage for the bytes, a table metadata layer for the transactions, and independent query engines on top — a combination rather than a product.
How Iceberg, Delta and Hudi turn immutable objects into a transactional table: a manifest of which files are the table now, and a commit that is one pointer swap.
A comparison across data types, query patterns, governance, cost shape, openness, transactions and tooling — with the vendor framing removed and the overlap admitted.
Buckets, keys, objects and metadata — and the four properties of that model that decide how every data pipeline above it must be written.
A narrow, purpose-built, usually pre-aggregated serving copy that trades flexibility and freshness for query cost and simplicity.
Scale each independently, point many engines at one copy, pay for compute only while it runs — and pay a network, a cold start and the loss of locality for it.