--- title: "#aws-glue articles | Hashnode" description: "Explore 93 articles tagged #aws-glue on Hashnode. Tutorials, guides, and how-tos from the community." url: "https://hashnode.com/tag/aws-glue" --- Tag # #aws-glue 93 posts · 20 followers [Rahul R](https://hashnode.com/@rahul-data) · [13h ago](https://hashnode.com/posts/how-delta-lake-is-built-on-top-of-amazon-s3-understanding-the-architecture-behind-it/6af47b60c44e54ee6bdc37ab) ### [How Delta Lake Is Built on Top of Amazon S3: Understanding the Architecture Behind It](https://rahul-dataeng.hashnode.dev/how-delta-lake-is-built-on-top-of-amazon-s3-understanding-the-architecture-behind-it?utm_source=hashnode&utm_medium=feed) Understanding How Parquet Files and Transaction Logs Turn an S3 Data Lake into a Reliable Lakehouse. 8 min read · [rahul-dataeng.hashnode.dev](https://rahul-dataeng.hashnode.dev/how-delta-lake-is-built-on-top-of-amazon-s3-understanding-the-architecture-behind-it?utm_source=hashnode&utm_medium=feed) [Rahul R](https://hashnode.com/@rahul-data) · [Oct 16](https://hashnode.com/posts/stop-reprocessing-everything-build-incremental-data-pipelines-on-aws/6ad2479331452b2a696fe7f8) ### [Stop Reprocessing Everything: Build Incremental Data Pipelines on AWS](https://rahul-dataeng.hashnode.dev/stop-reprocessing-everything-build-incremental-data-pipelines-on-aws?utm_source=hashnode&utm_medium=feed) A Practical Guide to AWS Glue, PySpark, and S3 for Processing Only What Has Changed 12 min read · [rahul-dataeng.hashnode.dev](https://rahul-dataeng.hashnode.dev/stop-reprocessing-everything-build-incremental-data-pipelines-on-aws?utm_source=hashnode&utm_medium=feed) [Rahul R](https://hashnode.com/@rahul-data) · [Oct 12](https://hashnode.com/posts/when-delta-lake-jobs-collide-troubleshooting-concurrency-issues-in-aws-glue/6acca39ec13a8ac656801a58) ### [When Delta Lake Jobs Collide: Troubleshooting Concurrency Issues in AWS Glue](https://rahul-dataeng.hashnode.dev/when-delta-lake-jobs-collide-troubleshooting-concurrency-issues-in-aws-glue?utm_source=hashnode&utm_medium=feed) Learn why concurrent DELETE, UPDATE, and MERGE operations fail in Delta Lake, and discover practical ways to debug transaction conflicts, prevent overlapping writes, and build more reliable AWS Glue data pipelines. 10 min read · [rahul-dataeng.hashnode.dev](https://rahul-dataeng.hashnode.dev/when-delta-lake-jobs-collide-troubleshooting-concurrency-issues-in-aws-glue?utm_source=hashnode&utm_medium=feed) [areebakhizer7](https://hashnode.com/@areebakhizer) · [Sep 10](https://hashnode.com/posts/part-3-stage-by-stage-building-the-home-assistant-etl/6aa2d5061cfb7c13fc90e119) ### [Part 3 - Stage by Stage: Building the Home Assistant ETL](https://areebakhizer.hashnode.dev/part-3-stage-by-stage-building-the-home-assistant-etl?utm_source=hashnode&utm_medium=feed) Three nightly AWS Glue jobs clean, flatten, and roll up raw Home Assistant events into Parquet tables queryable via Athena. 7 min read · [areebakhizer.hashnode.dev](https://areebakhizer.hashnode.dev/part-3-stage-by-stage-building-the-home-assistant-etl?utm_source=hashnode&utm_medium=feed) [N Chandra Prakash Reddy](https://hashnode.com/@ChandraPrakash1996) · [Sep 5](https://hashnode.com/posts/from-data-lake-to-lakehouse-building-modern-analytics-platforms-on-aws-with-s3-tables-aws-glue/6a9c052d3cb74146e2577854) ### [From Data Lake to Lakehouse: Building Modern Analytics Platforms on AWS with S3 Tables & AWS Glue](https://devopstour.hashnode.dev/from-data-lake-to-lakehouse-building-modern-analytics-platforms-on-aws-with-s3-tables-aws-glue?utm_source=hashnode&utm_medium=feed) Key insights from AWS Community Day Chennai | March 7, 2026 11 min read · [devopstour.hashnode.dev](https://devopstour.hashnode.dev/from-data-lake-to-lakehouse-building-modern-analytics-platforms-on-aws-with-s3-tables-aws-glue?utm_source=hashnode&utm_medium=feed) [Manu Shukla](https://hashnode.com/@mr-manushukla) · [Aug 21](https://hashnode.com/posts/aws-glue-60-cut-the-spark-dpu-rate-30-to-0308-but-only-on-60/6a88ab94ef03b0e7c7da5fb4) ### [AWS Glue 6.0 cut the Spark DPU rate 30% to $0.308, but only on 6.0](https://ecorpit.hashnode.dev/aws-glue-60-cut-the-spark-dpu-rate-30-to-0308-but-only-on-60?utm_source=hashnode&utm_medium=feed) AWS Glue 6.0 cut the Spark DPU rate 30% to $0.308, but only on 6.0 Summary. AWS Glue 6.0 became generally available on 21 August 2026 with what the announcement calls a 30% price reduction. The number 14 min read · [ecorpit.hashnode.dev](https://ecorpit.hashnode.dev/aws-glue-60-cut-the-spark-dpu-rate-30-to-0308-but-only-on-60?utm_source=hashnode&utm_medium=feed) [Prakash Agrawal](https://hashnode.com/@PrakashAgrawal) · [Jul 24](https://hashnode.com/posts/etl-configuration-with-s3-glue-studio-and-athena-in-aws/6a6303384cd322ce6b32b640) ### [ETL Configuration with S3, Glue Studio and Athena in AWS](https://prakashagrawal.hashnode.dev/etl-configuration-with-s3-glue-studio-and-athena-in-aws?utm_source=hashnode&utm_medium=feed) AWS ETL with AWS Glue 7 min read · [prakashagrawal.hashnode.dev](https://prakashagrawal.hashnode.dev/etl-configuration-with-s3-glue-studio-and-athena-in-aws?utm_source=hashnode&utm_medium=feed) [SapotaCorp](https://hashnode.com/@sapotacorpvn) · [Jul 12](https://hashnode.com/posts/data-engineering-for-a-regulated-fintech-a-10-month-aws-lake-build/6a53c5a0b98c9bd29bc95daf) ### [Data engineering for a regulated fintech: a 10-month AWS lake build](https://sapotacorpvn.hashnode.dev/data-engineering-for-a-regulated-fintech-a-10-month-aws-lake-build?utm_source=hashnode&utm_medium=feed) A regional fintech operator needed its legacy file submission and reporting platform rebuilt on a modern AWS data lake. We delivered a Medallion architecture on S3 + Glue + Airflow + Athena across two AWS accounts, with regulator-aligned co 13 min read · [sapotacorpvn.hashnode.dev](https://sapotacorpvn.hashnode.dev/data-engineering-for-a-regulated-fintech-a-10-month-aws-lake-build?utm_source=hashnode&utm_medium=feed) [SapotaCorp](https://hashnode.com/@sapotacorpvn) · [Jul 12](https://hashnode.com/posts/ingesting-every-partners-file-format-without-rewriting-code-each-time/6a53c3cec3b619f075b78e85) ### [Ingesting every partner's file format without rewriting code each time](https://sapotacorpvn.hashnode.dev/ingesting-every-partners-file-format-without-rewriting-code-each-time?utm_source=hashnode&utm_medium=feed) Every new data partner sends a different file: different columns, different order, different format. Hard-code a parser per partner and your codebase balloons and your pipeline cannot scale. Worse, when a file breaks at three in the morning 7 min read · [sapotacorpvn.hashnode.dev](https://sapotacorpvn.hashnode.dev/ingesting-every-partners-file-format-without-rewriting-code-each-time?utm_source=hashnode&utm_medium=feed) [SapotaCorp](https://hashnode.com/@sapotacorpvn) · [Jul 12](https://hashnode.com/posts/validating-data-against-its-own-history-baseline-data-quality-with-gluedq/6a53822612f045c55e25d084) ### [Validating Data Against Its Own History: Baseline Data Quality with GlueDQ](https://sapotacorpvn.hashnode.dev/validating-data-against-its-own-history-baseline-data-quality-with-gluedq?utm_source=hashnode&utm_medium=feed) Row level checks catch nulls and bad types, but they wave through data that is well formed yet wrong, like a contributor whose arrears drop 90 percent in a month. The fix is a Hybrid Baseline check that validates each batch against its own 8 min read · [sapotacorpvn.hashnode.dev](https://sapotacorpvn.hashnode.dev/validating-data-against-its-own-history-baseline-data-quality-with-gluedq?utm_source=hashnode&utm_medium=feed)