1. Merge-on-Read vs Copy-on-Write in Apache Iceberg
What is the difference between merge-on-read and copy-on-write in Apache Iceberg?
The author says that Apache Iceberg’s Merge-on-Read and Copy-on-Write approaches offer a nuanced balance between rapid updates and seamless reads. Discover why this dynamic is not only intellectually compelling but also critical for modern data challenges.
https://olake.io/iceberg/mor-vs-cow
2. Apache Iceberg Copy-On-Write (COW) vs Merge-On-Read (MOR): A Deep Dive
Apache Iceberg: Should you choose copy-on-write or merge-on-read?
In this article, Dani Pálma explores Copy-On-Write (COW) and Merge-On-Read (MOR), two approaches with distinct trade-offs in speed, storage, and efficiency. With PySpark examples and real-world insights, this deep dive helps you pick the best strategy for your data workloads.
https://estuary.dev/blog/apache-iceberg-cow-vs-mor/
3. Iceberg Catalog Showdown: Apache Polaris vs Unity Catalog
How do Apache Polaris and Unity Catalog compare when managing iceberg tables?
In this article, Karen Zhang explores Apache Polaris and Unity Catalog, two powerful data catalogs shaping the future of cloud data management. Polaris offers multi-engine flexibility, while Unity Catalog seamlessly integrates with Databricks, but which one is right for your architecture?
https://estuary.dev/blog/iceberg-catalog-apache-polaris-vs-unity-catalog/
4. Introducing Serverless Batch Inference
How do you run large-scale llm batch inference with zero setup?
This article introduces serverless AI functions, enabling effortless, 10x faster batch inference directly in Databricks. There is no infrastructure to manage, just seamless AI-powered workflows.
https://www.databricks.com/blog/introducing-serverless-batch-inference
5. Title Launch Observability at Netflix Scale
How does Netflix monitor and scale observability for millions of users?
The author, Varun Khaitan, explores how Netflix scales observability for title launches, from real-time monitoring to "Time Travel" simulations that catch issues before they happen. With Kafka queues, Hollow Feeds, and proactive insights, Netflix ensures every story reaches its audience seamlessly.
https://netflixtechblog.com/title-launch-observability-at-netflix-scale-8efe69ebd653
All rights reserved Den Digital, India. I have provided links for informational purposes and do not suggest endorsement. All views expressed in this newsletter are my own and do not represent current, former, or future employer” opinions.