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Cloud · Extra High-Value

Data lake vs data warehouse

Easycloud-25
data lakedata warehouselakehousearchitecture

Question

What is the difference between a data lake and a data warehouse?

Solution

A data lake stores broad data (structured, semi-structured, unstructured) as files on object storage for flexible processing.

A data warehouse stores curated, structured tables optimized for fast SQL analytics and BI (Redshift, BigQuery, Snowflake, Synapse).

Lake:       cheap files  -->  many engines  -->  flexible / raw+curated
Warehouse:  governed tables --> SQL/BI     -->  fast aggregates / marts

Comparison

| | Data lake | Data warehouse | |---|---|---| | Storage | Object store files | Managed tables (often columnar) | | Schema | Schema-on-read common | Schema-on-write / strongly typed | | Users | DE, ML, science | Analysts, BI, SQL | | Strength | Cheap retention, flexibility | Performance, governance for BI | | Weakness | Can become messy | Cost / rigidity for raw dumps |

Modern note

Lakehouse patterns (Delta/Iceberg + warehouse-style SQL) blur the line: warehouse reliability on lake storage.

Interview tip: Lake = flexible cheap landing; warehouse = curated SQL serving. Many stacks use both: lake for raw/replay, warehouse/marts for BI.

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