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My learningSnowflake Interview QuestionsLesson 09
Is Snowflake a Data Warehouse, Data Lake, or Lakehouse?

Lesson 09

Is Snowflake a Data Warehouse, Data Lake, or Lakehouse?

Snowflake started as a cloud data warehouse but has evolved into a modern data cloud platform with lakehouse capabilities. It supports structured, semi-structured, and unstructured data, enabling analytics, data engineering, AI, and data sharing from a single platform—combining features of both data warehouses and data lakes.

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Curriculum

15 lessons · 30m

0/15 lessons done30m left
  1. 01:56

    What Is Snowflake and What Problem Does It Solve?

    01:56

  2. 02:12

    Why Snowflake Is Called a Cloud-Native Data Warehouse

    02:12

  3. 01:48

    Snowflake on AWS, Azure & Google Cloud: How Multi-Cloud Works

    01:48

  4. 02:05

    Snowflake vs Traditional Data Warehouses: Teradata & Oracle Exadata Explained

    02:05

  5. 01:58

    Snowflake vs BigQuery vs Redshift vs Databricks: When to Choose Each Platform

    01:58

  6. 01:56

    Snowflake Account vs Database: What’s the Difference?

    01:56

  7. 02:01

    Snowflake Core Objects Explained: Databases, Schemas, Tables & Stages

    02:01

  8. 01:55

    Snowflake Editions Explained: Standard vs Enterprise vs Business Critical vs VPS

    01:55

  9. 02:02

    Is Snowflake a Data Warehouse, Data Lake, or Lakehouse?

    02:02

  10. 01:58

    Programming Languages Supported in Snowflake Today

    01:58

  11. 01:59

    Snowflake’s Three-Layer Architecture Explained: Storage, Compute & Cloud Services

    01:59

  12. 02:02

    Separation of Storage and Compute in Snowflake: Why It Matters

    02:02

  13. 02:12

    Snowflake Cloud Services Layer: Roles and Responsibilities

    02:12

  14. 01:54

    Where Snowflake Stores Data Physically in the Cloud?

    01:54

  15. 02:04

    What are micro-partitions, and how do they differ from traditional database partitions_

    02:04