I don't care about your database benchmarks (and neither should you)

Convex's approach to database performance emphasizes practicality over engaging in "bar chart wars" or synthetic benchmarks, which the team views as misleading and counterproductive. The company, with a strong background in building scalable systems, argues that comparing different database benchmarks is often futile due to the inherent differences in system designs and configurations, which lead to varied performance outcomes. Instead of focusing on theoretical maximum performance, Convex prioritizes scaling based on real customer needs and feedback, ensuring their platform is reliable, economical, and productive for actual use cases. To provide transparency, Convex plans to publish metrics based on real customer scenarios that reflect their platform's performance and cost, catering to future customer projections rather than competing in arbitrary benchmarks. This strategy aligns with their goal of delivering an effective and scalable platform for building full-stack AI projects while maintaining a clear focus on customer satisfaction and practical application.

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