AWS Q data integration

You can now generate data integration jobs for various data sources and destinations, including Amazon Simple Storage Service (Amazon S3) data lakes with popular file formats like CSV, JSON, and Parquet, as well as modern table formats such as Apache Hudi, Delta, and Apache Iceberg. Amazon Q can generate ETL jobs for connecting to over 20 different data sources, including relational databases like PostgreSQL, MySQL and Oracle; data warehouses like Amazon Redshift, Snowflake, and Google BigQuery; NoSQL databases like Amazon DynamoDB, MongoDB, and OpenSearch; tables defined in the AWS Glue Data Catalog; and custom user-supplied JDBC and Spark connectors. Your generated jobs can use a variety of data transformations, including filters, projections, unions, joins, and aggregations, giving you the flexibility to handle complex data processing requirements.

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Tech tags:

• Data injection
• Data transformation

Related shared contents:

• Amazon Q data integration adds DataFrame support and in-prompt context-aware job creation
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  2024-12-20

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