Gartner Research

Data Hubs, Data Lakes and Data Warehouses: How They Are Different and Why They Are Better Together

Summary

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.

Published: 13 February 2020

ID: G00465401

Analyst(s): Ted Friedman Nick Heudecker

Table Of Contents
  • Key Challenges

Introduction

Analysis

  • Distinguish Between Data Warehouses, Data Lakes and Data Hubs, and Recognize How They Differ in Focus
  • Communicate the Characteristics and Common Use Cases for Each of These Structures
  • Maximize Your Ability to Support a Broader Range of Diverse Use Cases Through Combinations of These Structures

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