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Cost-effective ETL with DuckDB and Amazon S3 Tables on AWS Glue

Learn how to pair DuckDB with AWS Glue 6.0 to run SQL-centric ETL on a single worker, reading Parquet from Amazon S3 and writing Apache Iceberg tables to Amazon S3 Tables. This post walks through a complete, runnable example and compares measured cost and runtime against an equiv

At a glance

Where	AWS

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Last sweep 2026-10-24: 0 finding(s), 0 marked as examples.

Registry stats

Verification	community
Completeness	47
Trust multiplier	×0.63
Composite	23.55 · unproven
License	Proprietary
Security flags	none

Marketplace Quality Score

unproven (23.55/100)

Rule-based scoring across 7 dimensions. Higher is better. How it works

performance /100

completeness 47/100

test coverage 5/100

security 90/100

documentation 20/100

maintainability 0/100

community /100

Metadata

Category: AWS
Stage: Cloud
License: Proprietary
Publisher: AWS Big Data Blog
Source: https://aws.amazon.com/blogs/big-data/cost-effective-etl-with-duckdb-and-amazon-s3-tables-on-aws-glue/

Security Posture (0)

A listing is not an endorsement. Review the flags before connecting.

runs code: —
network access: —
credentials: —
filesystem access: —
external apis: —

Provenance

Verification: community
Evidence: 1/10 checks · earned community
Stale: Last verified days ago (>180 days)
Source File: data/curated/references/2026-10-09-cost-effective-etl-with-duckdb-and-amazon-s3-tables-on-aws-glue.yaml

Before you trust this

Limitations: No documented limitations — treat the unknown as unknown, not as safe.
Prerequisites: None declared
Evidence checklist: source reachable: unclaimedmetadata validated: passedlicense reviewed: unclaimedtutorial generated: unclaimedstatic checks passed: unclaimedbuild passed: unclaimedtests passed: unclaimedsmoke passed: unclaimedoutput validated: unclaimedsecurity reviewed: unclaimed

Related in the graph (5)

AWS Glue Documentation (Reference)
Materialize once, query anywhere: Introducing Iceberg materialized views in Amazon Redshift (Reference)
AWS Architecture Reviewer (Agent)
AWS MCP Servers (Labs) (MCP server)
S3 → Glue → Athena (Project)

Computed from shared taxonomy — not curator endorsements.

Roadmap Alignment

Cloud (platforms)

This artifact teaches skills for the stages above in the 13-stage Data Engineering roadmap.

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Cost-effective ETL with DuckDB and Amazon S3 Tables on AWS Glue