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Warehousing & Analytics
Engage in discussions on data warehousing, analytics, and BI solutions within the Databricks Community. Share insights, tips, and best practices for leveraging data for informed decision-making.
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Comparison between parquet format and avro format

User16826994223
Databricks Employee
Databricks Employee
 
1 REPLY 1

User16826994223
Databricks Employee
Databricks Employee
  1. AVRO is a row-based storage format whereas PARQUET is a columnar based storage format.
  2. PARQUET is much better for analytical querying i.e. reads and querying are much more efficient than writing.
  3. Write operations in AVRO are better than in PARQUET.
  4. AVRO is much matured than PARQUET when it comes to schema evolution. PARQUET only supports schema append whereas AVRO supports a much-featured schema evolution i.e. adding or modifying columns.
  5. PARQUET is ideal for querying a subset of columns in a multi-column table. AVRO is ideal in case of ETL operations where we need to query all the columns.

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