Catch N+1 queries, memory leaks, and performance anti-patterns before they reach production. Save infrastructure costs. Works great with code quality checks.
Slow code costs money, frustrates users, and compounds over time. Track it alongside technical debt for full visibility.
88% of performance issues are discovered in production. Fixing them post-release is 10x harder and costs 100x more than catching at code review.
Teams overspend $50-200k/year on infrastructure to compensate for inefficient code. A single N+1 query can cost $10k/month in database load.
Only 15% of N+1 queries are caught in code review. Reviewers focus on correctness — memory leaks and O(n²) algorithms slip through 85% of the time.
Average app slows 23% per year from accumulated inefficiencies. Users abandon pages that take >3 seconds. 1 second delay = 7% conversion drop.
From database queries to frontend rendering — we catch it all
Database queries inside loops that should be batched
Unreleased resources, growing collections, event listeners
O(n²) algorithms when O(n) is possible
Synchronous I/O that should be async
React components re-rendering without memo
Importing entire libraries when tree-shaking available
diffray understands popular ORMs and detects N+1 queries, missing eager loading, and inefficient query patterns specific to your stack.
// 100 users = 101 queries
users.forEach(user => user.posts)
// 2000ms response time
// 100 users = 2 queries
users.include(:posts).each...
// 50ms response time
Performance rules tailored to your tech stack
Catch performance issues before they reach production
Developer creates a pull request with new code
AI analyzes code for performance anti-patterns
Each issue includes severity and estimated impact
Get specific code changes to fix each issue
"diffray found 47 N+1 queries in our first week. Our API response times dropped from 2s to 200ms."
Michael Torres
Backend Lead, E-commerce Platform
"We reduced our AWS bill by 40% after fixing the performance issues diffray identified. It paid for itself in week one."
Lisa Chen
VP Engineering, Growth Startup
diffray detects N+1 queries, memory leaks, expensive loops, inefficient algorithms (O(n²) when O(n) is possible), missing indexes, synchronous operations that should be async, and resource-intensive operations in hot paths.
Runtime profiling shows issues after they happen. diffray catches performance problems at code review time, before the code is merged. This prevents performance regressions from ever reaching production.
Yes. diffray understands popular ORMs like Prisma, TypeORM, Sequelize, ActiveRecord, and Django ORM. It detects N+1 queries, missing eager loading, and inefficient query patterns specific to your ORM.
Yes. diffray detects React re-render issues, missing memoization, large bundle imports, inefficient CSS selectors, and other frontend performance anti-patterns.
diffray analyzes code paths to estimate impact. For N+1 queries, it calculates potential query count based on typical data volumes. For algorithms, it identifies Big O complexity. Each finding includes severity and estimated performance impact.
Absolutely. Teams typically see 20-40% infrastructure cost reduction after fixing issues diffray identifies. By catching inefficient code before production, you avoid scaling problems that require throwing more servers at slow code.
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