Improve DynamoDB analytics with AWS Glue zero-ETL schema and partition controls
Big Data Blog
This article explains how to use AWS Glue Zero-ETL to replicate DynamoDB data to Apache Iceberg tables in S3 for analytics, with configurable schema unnesting and data partitioning.
- AWS Glue Zero-ETL eliminates custom ETL pipelines for DynamoDB analytics workloads
- Schema unnesting flattens nested DynamoDB attributes into individual queryable columns
- Three unnesting options: no unnesting, unnest one level, or unnest all levels (default)
- Data partitioning organizes replicated data to enable partition pruning and reduce query costs
- Partitioning strategies: identity (low-cardinality columns), time-based (timestamps), multi-level
- Replication completes within 15 minutes; queries run directly in Amazon Athena
- Step-by-step walkthrough covers creating integration, configuring settings, and querying results
- Best practices include avoiding high-cardinality identity partitioning and matching timestamp formats
AWS Glue Zero-ETL simplifies DynamoDB analytics by automatically replicating semi-structured data to flat, queryable Iceberg tables with optimized schema and partitioning.
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