pandasanjay opened a new issue, #35196:
URL: https://github.com/apache/beam/issues/35196

   ### Is your feature request related to a problem?
   
   A clear and concise description of what the problem is. Ex. I'm always 
frustrated when [...]
   
   ### Describe the solution you'd like
   
   Support for a Storage Read API enrichment handler would be beneficial. This 
approach offers several advantages over traditional BigQuery SQL-based 
implementations:
   
   *   **Performance:** The Storage Read API provides a faster way to read data 
from BigQuery, especially for large datasets, as it streams data directly from 
storage without the overhead of SQL query execution.
   *   **Cost Efficiency:** By bypassing SQL query execution, it can lead to 
cost savings, particularly for high-volume read operations.
   *   **Scalability:** The direct stream access is inherently more scalable 
for high-throughput enrichment scenarios.
   *   **Flexibility:** It allows for more complex, programmatic data 
manipulation and enrichment logic that might be cumbersome or inefficient to 
express in SQL.
   
   ### Describe alternatives you've considered
   
   The current alternative is using traditional BigQuery SQL-based 
implementations for enrichment. 
https://github.com/apache/beam/blob/master/sdks/python/apache_beam/transforms/enrichment_handlers/bigquery.py
   
   ### Release note
   
   <!-- Now that you have thought about the problem, the solution and the 
alternatives, please provide a release note. This will help us prioritize the 
feature request. -->
   <!-- The release note should be written in the past tense and include a 
brief summary of the feature. -->
   <!-- It should be suitable for inclusion in the release notes of the next 
Apache Beam release. -->
   <!-- Example: Added support for X in Y. -->
   Added support for a Storage Read API enrichment handler, offering 
performance and cost benefits over traditional SQL-based BigQuery enrichment.
   
   ### Anything else?
   
   _No response_
   


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