Vinicius Grippa
Vinicius Grippa
Articles by Vinicius Grippa (6)
In this blog post, we are going to use "Vibe Coding" to build an application and explore Readyset QueryPilot, a tool designed to automatically analyze and cache queries in a MySQL workload. The goal is to prove that even for automated queries with no human interaction, QueryPilot can automate query caching and improve performance. QueryPilot automatically identifies which queries should be cached and recommends the appropriate strategy, either deep caching or shallow caching. This automation de
Database performance is often the bottleneck in high-traffic web applications. Whether you're serving user dashboards, product catalogs, or personalized content, the same SQL queries get executed repeatedly. Caching sounds like the natural solution. However, traditional caching can be challenging to implement correctly: you need to manually add cache logic to your application (such as Redis), keep cache entries in sync, and address edge cases like stale data. Readyset takes a different approach
Consider the perfect scenario: the database is running on reliable hardware, MySQL has been finely tuned, and queries have been reviewed and optimized. Despite this, sustained business growth inevitably leads to an increase in workload over time. When this happens, even optimized queries can begin to overwhelm the system, not because they are slow, but because they run frequently and consume cumulative resources over time. At this stage, optimizing performance goes beyond analyzing execution pl
Introduction It’s common for DBAs to optimize queries to address bottlenecks and reduce resource contention. However, in production workloads, the most resource-intensive queries aren’t always the longest-running ones. High-frequency queries that execute quickly but are called repeatedly can collectively consume significant resources, increasing overall latency and system load. Identifying these queries requires a more comprehensive analysis than simply inspecting the slow query log or process
Scaling relational databases in the cloud often creates a tension between cost and performance. As workloads grow—especially read-heavy ones powering analytics, dashboards, or reports—latency increases and infrastructure bills spike. The default response is usually vertical scaling: increase instance size, add more CPU and memory. While effective up to a point, this approach quickly hits diminishing returns and inflates costs. An alternative is horizontal scaling, traditionally achieved through
In our blog post on Optimizing SQL Pagination in Postgres, we explained how to optimize SQL pagination for Postgres. As a counterpart, we’ve decided to write one for MySQL pagination. Like PostgreSQL, MySQL offers several ways to handle pagination, but some are far more efficient than others. Let's break down the SQL Pagination options, talk about why LIMIT and OFFSET can be a problem, and look at smarter ways to paginate large datasets efficiently. The Classic SQL Pagination Approach: LIMIT
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