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infoq.com /1 month ago

Article: The Schema Proliferation Problem in Kafka and Flink Pipelines: How to Solve It

Schema proliferation builds slowly and gets expensive fast. One schema per event type feels right until there are ten tables, union queries spanning all of them, and a single field...

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dataengineeringcentral.substack.com /1 month ago

Databricks Zerobus - Event Streams + Lake House (be gone Kafka)

it's always something you know

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medinform.jmir.org /1 day ago

The Swiss Personalized Health Network Metadata Catalog: Platform for Health Data Discovery and Exploration Based on Find...

Background: The Swiss Personalized Health Network (SPHN) facilitates the interoperability and secure sharing of health-related data for research in Switzerland, in line with the fi...

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dev.to /2 weeks ago

What Is an MCP Registry? (And the NxM Problem It Solves)

TL;DR: An MCP registry is a centralized catalog of MCP servers - what they do, how to connect, what tools they expose, and who's authorized to call them. Without one, every develop...

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dzone.com /1 month ago

Building a Reusable Framework to Standardize API Ingestion in an On-Prem Lakehouse

In many enterprise lakehouse environments, the biggest ingestion challenge is not data volume; it is inconsistency. As platforms grow, data starts arriving from many different syst...

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javacodegeeks.com /1 week ago

The Hidden Complexity of Schema Evolution: How Data Outlives the Code That Created It

A theoretical framework for thinking about backward and forward compatibility across Avro, Protobuf, JSON, and relational schemas — before a breaking change reaches production. Cod...

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