TiDB

Key Moments HTAP already unifies transactional and analytical data, years before LTAP framed it as unsolved. Every AI agent mixes transactional and analytical work in one loop, which makes it an HTAP workload. For autonomous agents, inconsistent data isn’t just lag, it’s incorrect reasoning.

When

Key Takeaways Coding is dead means the code is no longer the artifact that matters. The verified outcome is. An agent is a runtime, skills, and an environment. The environment is the part everyone ignores and the part that matters most. Agent workloads invert the scale problem: Not one dataset too large for one machine, but

Key Takeaways Choosing a database for scale is a ten-year decision that caps how far you can grow. As capabilities converge, buyers choose on taste and judgment. The primary user is now the agent, not the human. Hence one agent, one database. ...

Key Takeaways NCC Group’s 45-day white-box assessment found zero critical, high, or medium severity issues across 20 repositories. All eight findings were rated Low, spanning default configuration hardening and dependency hygiene. TiDB integrated gosec into CI, updated dependencies, and NCC Group verified that mTLS an...

Key Takeaways Amazon Aurora writes run on one primary instance. The largest, db.r8g.48xlarge, is the ceiling. Read replicas and Serverless v2 add no write capacity; sharding does, but you maintain it. Amazon Aurora Limitless scales writes only for PostgreSQL, not Aurora MySQL. TiDB scales writes by adding nodes and speaks MySQL, so no app rewrite. ...