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What is the difference between Managed and External Tables in Databricks?

Spark/Big Dataeasy0.6 min readPremium
Frequency
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Asked at 2 companies
Category
452
questions in Spark/Big Data
Difficulty Split
88E|81M|283H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
AltimetrikIncedo
Key Concepts Tested
snowflakespark
Expert AnswerPremium
125 wordsInterview-ready
**Managed tables**: Databricks/Spark owns both metadata and data; `DROP TABLE` deletes metadata and underlying data. **External tables**: Metadata is in the catalog; data lives in an external location (S3, ADLS, GCS); `DROP TABLE` removes only metadata; data persists. **Why it matters architecturally**: Managed tables enforce a single lifecycle for schema and data. External tables decouple storage from compute, enabling multi-engine access (Snowflake, Athena, Redshift) and shared data lakes....
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