Many data and analytics leaders think of data hubs, data lakes and data warehouses as interchangeable alternatives. In reality, each of these architectural patterns has a different primary purpose. When they are combined, they can support increasingly complex, diverse and distributed workloads.
“Data warehouses and data lakes are structures supporting analytic workloads. Data hubs are different — their main focus is enabling data sharing and governance.”
– Ted Friedman and Nick Heudecker, Gartner
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