Data and AI releases

This month963Companies169

963 this month · 169 companies

Amazon EMR now supports native data quality checks in Apache Spark jobs

UpdateyesterdayUnverifiedAdded Oct 13, 2026

Amazon EMR now validates data quality natively within Apache Spark jobs. Data engineering teams can catch quality issues inline before bad data reaches downstream systems, without building or maintaining separate validation infrastructure.

Topics: Streaming, Governance, Pricing, Data integration, Apache Iceberg

AWS's release notes

More AWS Glue and Lake Formation releases

Every AWS Glue and Lake Formation release
Updateunverified

Apache Iceberg materialized views now support system-managed write protection

Today, AWS announces system-managed materialized views for Apache Iceberg. Materialized views let you precompute an expensive query once and reuse the result across engines. Because this result is an open Iceberg table in your data lake, anyone with write access can change it, either through the catalog or by writing to the files in Amazon S3.

Updateunverified

AWS Glue Data Quality delivers context-specific rule recommendations in seconds

AWS Glue Data Quality now generates data quality rules in seconds, reducing the time to establish data quality checks for your tables in the AWS Glue Data Catalog. You get a ready-to-use set of rules with full coverage across every column, with no manual setup, so you can move from raw data to trusted data faster while authoring pipelines.

Update

AWS Glue zero-ETL now captures archived Salesforce records

AWS Glue zero-ETL integrations for Salesforce now capture archived records in your target tables, giving you a complete replica of your Salesforce data for analytics and reporting. Archived records are identified and reflected accurately through the isArchived field, so your analytical data stays fully in sync with your Salesforce source.

Also shipped on Oct 12, 2026

AWS in October 2026