PingCAP’s Top 10 Posts of 2020

Author: PingCAP

Editors: Caitin Chen, Tom Dewan

2020 has been a difficult year for everyone, but at PingCAP we continued to innovate and inform. This year, we released TiDB 4.0, a real-time Hybrid Transactional/Analytical Processing (HTAP) database, and we published 50+ technical blog posts and 17 case studies. We’d like to thank all our TiDB contributors and users for their trust and support. They not only helped us improve our product, but they also contributed great material for many of our excellent articles.

From pondering the future of databases, to intrepid bug hunters, to TiDB case studies, let’s take a look back at our 10 most popular posts in 2020:

• A Peek into the Future of Database: A Unified Infrastructure to Adapt Intelligently

  What principles will influence the database of the future? In this post, Ed Huang, PingCAP’s CTO, suggests that the key drivers will be unification, adaptiveness, and intelligence.

• Lessons from TiDB’s No. 1 Bug Hunters Who’ve Found 400+ Bugs in Popular DBMSs

  Dr. Manuel Rigger and his colleague have found 400+ bugs in popular DBMSs, including 50+ TiDB bugs. Learn their techniques for finding logic bugs in DBMSs.

• Embracing NewSQL: Why We Chose TiDB over MongoDB and MySQL

  In this post, PalFish explained why they chose TiDB over MongoDB and MySQL. The key factors were their application requirements and their perspective on NewSQL databases.

• Apache Flink + TiDB: A Scale-Out Real-Time Data Warehouse for Analytics Within Seconds

  Do you think a real-time data warehouse’s architecture is complex and hard to maintain? Not necessarily. By combining Apache Flink and TiDB, we offer an efficient, easy-to-use, real-time data warehouse with horizontal scalability and high availability.

• Why We Chose a Distributed SQL Database to Complement MySQL

  VIPKid chose TiDB to manage its high data volume, highly concurrent write application. Learn how TiDB excels in that scenario, along with multidimensional queries, data life cycle management, and real-time analytics.

• A 3x IT Efficiency Boost: Using a Scale-Out HTAP Database for Near Real-Time Analytics

  As its business quickly grew, ZTO Express found Exadata, Kudu, and HBase couldn’t meet their database requirements. To scale out their database and perform multi-dimensional analytics in near real time, they migrated from Oracle Exadata to TiDB.

• Key Visualizer: Observe Distributed Databases to Discover the Unknowns

  Key Visualizer is a visual diagnostic tool that makes it easier to troubleshoot distributed SQL databases. Users can observe system health, quickly find hotspots in the cluster, and gain deep insights into applications.

• How to Trace Linux System Calls in Production with Minimal Impact on Performance

  To trace system calls in Linux effectively, you can use perf to analyze system calls that have latency in general scenarios. For containers or Kubernetes that use cgroup v2, traceloop is more convenient.

• Generics and Compile-Time in Rust

  In part 2 of the Rust Compile Time series, Brian Anderson, one of Rust’s original authors, talked about monomorphization, using the TiKV project as a case study.

• Early Impressions of Go from a Rust Programmer

  Nick Cameron, a long-time Rust programmer, talked about his early impressions of Go.