<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Managed-Service on nanta - Data Engineering</title><link>https://nanta-data.dev/en/tags/managed-service/</link><description>Recent content in Managed-Service on nanta - Data Engineering</description><generator>Hugo -- gohugo.io</generator><language>en</language><copyright>© 2026 nanta</copyright><lastBuildDate>Fri, 27 Feb 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://nanta-data.dev/en/tags/managed-service/index.xml" rel="self" type="application/rss+xml"/><item><title>S3 Table Buckets PoC: Evaluating Managed Iceberg for CDC Workloads</title><link>https://nanta-data.dev/en/posts/s3-table-buckets-poc/</link><pubDate>Fri, 27 Feb 2026 00:00:00 +0000</pubDate><guid>https://nanta-data.dev/en/posts/s3-table-buckets-poc/</guid><description>AWS S3 Table Buckets offer managed Iceberg tables with automatic compaction. We ran a PoC to see if they could solve our CDC table compaction problem. We validated Trino, Spark, and Kafka Connect integration, examined auto-compaction behavior, and assessed costs. The conclusion: not a fit for every table, but valuable specifically for CDC workloads with unpredictable partition-level updates.</description></item></channel></rss>