Blogs by: Dmitrii Sherstobitov

Benchmarking AI Coding Agents for Distributed SQL: What We Learned

Benchmarking AI Coding Agents for Distributed SQL: What We Learned

AI models write vanilla PostgreSQL. If your database is distributed, providing the AI model with a YugabyteDB skill file closes the gap and ensures it writes code that works for your application. In this blog, we break down the benchmarking results across 17 model configurations. We conducted 350+ evaluations across Claude 4.5, 4.6, and 4.7, Gemini 3.1 Pro, GPT-5.x, Composer 2, Codex CLI – through Claude Code CLI, Cursor, and Codex. Discover what moved the score, what regressed, and the one structural finding that changes how every team should think about delivering context to an AI coding tool.

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Embracing Chaos: Testing Resiliency and Consistency in YugabyteDB

Embracing Chaos: Testing Resiliency and Consistency in YugabyteDB

Jepsen tests and a chaos-driven testing framework play a crucial role in identifying and addressing vulnerabilities. However, traditional testing methods fall short for cloud-native applications and distributed systems. This blog provides the latest Jepsen updates for YugabyteDB, as well as sharing information on additional in-house built frameworks for resiliency and consistency testing that go far beyond Jepsen.

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