How We Reduced Online Serving Latency From 1.11s to 123.6ms With a Distributed SQL Database

This post tells how a website with a distributed database reduced online serving latency from 1.11 s to 417.7 ms, and then to 123.6 ms. We found that some lessons learned on MySQL could be applied throughout the optimization process. But when we optimize a distributed database, we need to consider more.

The OSS Insight website displays the data changes of GitHub events in real time. It's powered by TiDB Cloud, a MySQL-compatible distributed SQL database for elastic scale and real-time analytics.

Packages for Store Routines in MariaDB 11.4
No categories
MariaDB 11.4 introduced many advanced features. One that grabbed my attention is the general support of packages for stored routines. Although this was previously available by activating the Oracle compatibility mode, now the feature is available gener... […]
Maintain Chat History in Generative AI Apps With Valkey
No categories
A while back I wrote up a blog post on how to use Redis as a chat history component with LangChain. Since LangChain already had Redis chat history available as a component, it was quite convenient to write a client application. But, that's not the same... […]
Knowledge Graph Enlightenment, AI, and RAG
No categories
In the previous edition of the YotG newsletter, the wave of Generative AI hype was probably at its all-time high. Today, while Generative AI is still talked about and trialed, the hype is subsiding. Skepticism is settling in, and for good reason. Repor... […]
Building an Effective Zero Trust Security Strategy for End-To-End Cyber Risk Management
No categories
You've probably heard a lot about zero-trust security lately, and for good reason. As we move more of our applications and data to the cloud, the traditional castle-and-moat approach to security just doesn't cut it anymore. This makes me come... […]
Phased Approach to Data Warehouse Modernization
No categories
A modernized database will help you focus on building innovative solutions rather than investing your time and effort in managing these legacy systems. Based on the scale of your existing data warehouse processes or jobs, it can be an enormous task to ... […]