Weekend Reading #66

Weekend Reading: A weekly roundup of interesting Software Architecture and Programming articles from tech companies. Find fresh ideas and insights every weekend.

This week: NoSQL interview questions and answers, YouTube Shorts generation via AI, Pinterest’s recommendation quality improvements, and Uber’s real-time OLAP with Apache Pinot.

Part 8: NoSQL Databases – C# / .NET Interview Questions and Answers

👉 Useful if you’re preparing for backend interviews or revising NoSQL fundamentals.

A structured set of NoSQL interview questions covering document, key-value, vector, and graph databases. Focuses on trade-offs, use cases, and real-world design decisions.

How I Built an AI-Powered YouTube Shorts Generator

👉 Interesting if you’re curious how to build similar products using AI

The author explains how he built a tool that analyzes long YouTube videos using LLM technology and produces 5-10 ready-to-publish YouTube Shorts.

Improving Quality of Recommended Content through Pinner Surveys

👉 Good read if you work on recommender systems or ML evaluation.

Pinterest explains how user surveys are used to train and evaluate recommendation models. The approach helps align ML predictions with absolute user satisfaction.

Blazing Fast OLAP on Uber’s Inventory and Catalog Data with Apache Pinot

👉 Great if you’re interested in OLAP engines or real-time analytics architecture.

Uber engineers show how Apache Pinot powers low-latency analytics on inventory and catalog data. The system supports real-time queries at a massive scale.