Bigtable
Introduction In today’s fast-paced, data-driven environment, the ability to process, analyze, and act on massive amounts of data in real time is critical. For businesses striving to deliver personalized customer experiences and streamline operations, choosing the right database technology is a key strategic decision. At Zeotap — a leading Customer
logging systems
# Introduction *"Our logging system burns through 100,000 RMB every month. Is that normal?"* — This was the sobering question posed by a CTO in a tech chat group last year. As an architect with eight years in the logging domain, I’ve seen countless teams make costly mistakes:
Apache Kafka
# 1. Kafka: The Bridge Between Data Operations and Data Analytics I’ve worked with **Apache Kafka** for many years and have developed a deep respect for its capabilities. As a data engineer, I often use it as a **bridge** between **data operations** and **data analytics**. Its elegant distributed log design
google cloud
# Benchmarking GPT OSS on Google Cloud C4 VMs with Intel® Xeon® 6 (Granite Rapids) Intel and Hugging Face partnered to demonstrate **real-world performance gains** from upgrading to **Google’s new C4 Virtual Machine (VM)**, powered by **Intel® Xeon® 6 processors (codenamed Granite Rapids – GNR)**. They benchmarked the **OpenAI GPT OSS