AWS Data Analytics Pipeline

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About This Architecture

Serverless data analytics pipeline extracts operational data from Amazon RDS PostgreSQL using AWS Glue incremental ETL jobs. Transformed data lands in Amazon S3 as partitioned Parquet files, optimized for columnar queries. Amazon Athena provides SQL access to the data lake, feeding Amazon QuickSight dashboards with SPICE in-memory acceleration and Q natural language chatbot for business users. This architecture eliminates infrastructure management while enabling cost-effective analytics at scale, ideal for teams migrating from monolithic data warehouses to modern lake-house patterns.

People also ask

How do I build a serverless data analytics pipeline on AWS from RDS to QuickSight?

Use AWS Glue incremental ETL to extract from RDS PostgreSQL, store as partitioned Parquet in S3, query with Athena, and visualize in QuickSight with SPICE in-memory engine and Q natural language chatbot. This diagram shows the complete serverless architecture.

AWS Data Analytics Pipeline

AWSintermediateData EngineeringETLServerlessAnalyticsLake-house
Domain: Data EngineeringAudience: data engineers building serverless analytics pipelines on AWS
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Created by

February 20, 2026

Updated

March 17, 2026 at 12:36 AM

Type

architecture

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