When would you use AWS Glue for transformation and when would you use Snowflake?
💡 Model Answer
AWS Glue is a serverless ETL service that automatically discovers data, generates ETL code, and runs jobs on a managed Spark cluster. It is ideal for extracting data from sources such as S3, RDS, or JDBC, transforming it with Spark or Python, and loading it into a data lake or warehouse. Snowflake, on the other hand, is a cloud data warehouse that separates compute and storage, supports ANSI SQL, and offers instant scaling and concurrency. Use Glue when you need to ingest, clean, and transform raw data before it reaches a warehouse, especially if you want a fully managed Spark environment. Use Snowflake when you need a high-performance, columnar store for analytics, reporting, and BI workloads. In many pipelines, Glue can prepare the data and then load it into Snowflake for downstream analytics.
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