Cursor storage

SQLite Database Locking and Concurrency Errors After Cursor Build

Your Cursor-generated application uses SQLite as its database and works fine during development with a single user, but fails with SQLITE_BUSY or "database is locked" errors as soon as multiple users access it simultaneously. Write operations timeout, reads sometimes return stale data, and the app becomes unreliable under any real load.

Cursor frequently chooses SQLite because it's the simplest database to set up — no server to configure, just a file. But SQLite's concurrency model is fundamentally different from PostgreSQL or MySQL. It uses file-level locking, meaning only one write can happen at a time, and readers can block writers depending on the journal mode.

This issue typically surfaces immediately after deploying to production or during load testing when more than a handful of concurrent users interact with the application.

Error Messages You Might See

SQLITE_BUSY: database is locked SQLITE_LOCKED: database table is locked Error: SQLITE_BUSY (database is locked) OperationalError: database is locked SqliteError: database is locked - WAL mode
SQLITE_BUSY: database is lockedSQLITE_LOCKED: database table is lockedError: SQLITE_BUSY (database is locked)OperationalError: database is lockedSqliteError: database is locked - WAL mode

Common Causes

  • Default journal mode (DELETE) — SQLite's default journal mode allows only one writer at a time and blocks all readers during writes
  • Multiple connections without WAL mode — Each request opens a new connection but WAL (Write-Ahead Logging) mode isn't enabled, causing lock contention
  • Long-running transactions — Cursor generated code that holds database locks during slow operations (API calls, file processing) within a transaction
  • Concurrent writes from multiple processes — Serverless or multi-process deployments create multiple processes all trying to write to the same SQLite file
  • No busy timeout configured — The default busy timeout is 0ms, meaning any lock contention immediately throws an error instead of retrying

How to Fix It

  1. Enable WAL mode — Run PRAGMA journal_mode=WAL; on your database connection. WAL allows concurrent readers and a single writer, dramatically improving performance
  2. Set a busy timeout — Configure PRAGMA busy_timeout=5000; to wait up to 5 seconds for locks instead of immediately failing
  3. Use a single connection with serialization — For web apps, use a connection pool of size 1 with a write queue, or use better-sqlite3 (synchronous) instead of sqlite3 (async) in Node.js
  4. Keep transactions short — Never do network calls, file I/O, or heavy computation inside a database transaction. Read data, release the lock, process, then write back
  5. Consider migrating to PostgreSQL — If your app needs real concurrent access, SQLite may not be the right choice. Use PostgreSQL or MySQL with a connection pool
  6. Move SQLite to a persistent volume — If staying with SQLite, ensure the database file is on a persistent volume, not ephemeral serverless storage

Real developers can help you.

Dor Yaloz Dor Yaloz SW engineer with 6+ years of experience, I worked with React/Node/Python did projects with React+Capacitor.js for ios Supabase expert Prakash Prajapati Prakash Prajapati I’m a Senior Python Developer specializing in building secure, scalable, and highly available systems. I work primarily with Python, Django, FastAPI, Docker, PostgreSQL, and modern AI tooling such as PydanticAI, focusing on clean architecture, strong design principles, and reliable DevOps practices. I enjoy solving complex engineering problems and designing systems that are maintainable, resilient, and built to scale. Kingsley Omage Kingsley Omage Fullstack software engineer passionate about AI Agents, blockchain, LLMs. Jacek Rozanski Jacek Rozanski Senior PHP/Symfony developer and DevOps engineer with 20+ years of professional experience, running opcode.pl (web development agency, est. 2004). Day job: I'm the sole backend developer at merketing company where I own and maintain 11 PHP/Symfony microservices on AWS (ECS Fargate, RDS, S3, CloudFront), handle the full CI/CD pipeline (Bitbucket Pipelines, Docker), and manage monitoring with Sentry and CloudWatch. These services handle high request volumes in production every month. What I bring to AI-built apps: - I audit and fix security issues (OWASP methodology), performance bottlenecks, and architectural problems in codebases generated by Cursor, Claude Code, Lovable, Bolt, and v0 - I refactor AI-generated prototypes into production-grade applications with proper error handling, testing, and clean architecture (SOLID, DDD, hexagonal architecture) - I set up the infrastructure AI tools don't touch: AWS hosting, CI/CD pipelines, automated deployments, database optimization, monitoring, and alerting - I integrate external services: payment providers, email systems, partner APIs, SSO/auth Tech stack: PHP 8.x, Symfony, React, Next.js, PostgreSQL, MySQL, Docker, AWS (ECS, RDS, S3, SQS/SNS, CloudFront), Terraform, Supabase. I also use AI tools daily (Claude Code, Cursor) in my own workflow, so I understand both the strengths and the gaps in AI-generated code. Based in Poland (CET timezone). Available for async work and calls during EU/US business hours. PawelPloszaj PawelPloszaj I'm fronted developer with 10+ years of experience with big projects. I have small backend background too Matthew Jordan Matthew Jordan I've been working at a large software company named Kainos for 2 years, and mainly specialise in Platform Engineering. I regularly enjoy working on software products outside of work, and I'm a huge fan of game development using Unity. I personally enjoy Python & C# in my spare time, but I also specialise in multiple different platform-related technologies from my day job. Matthew Butler Matthew Butler Systems Development Engineer @ Amazon Web Services Meïr Ankri Meïr Ankri Full-stack developer specializing in React / Next.js / Node.js with 6+ years of experience. I've worked across various sectors including automotive (Reezocar/Société Générale), healthcare (Medical Link SaaS), and e-commerce (Glasman). I build web apps end-to-end, from architecture to production, with a focus on scalability, performance, and code quality. I also mentor junior developers and contribute to technical decisions and code reviews. Caio Rodrigues Caio Rodrigues I'm a full-stack developer focused on building practical and scalable web applications. My main experience is with **React, TypeScript, and modern frontend architectures**, where I prioritize clean code, component reusability, and maintainable project structures. I have strong experience working with **dynamic forms, state management (Redux / React Hook Form), and complex data-driven interfaces**. I enjoy solving real-world problems by turning ideas into reliable software that companies can actually use in their daily operations. Beyond coding, I care about **software quality and architecture**, following best practices for componentization, code organization, and performance optimization. I'm also comfortable working across the stack when needed, integrating APIs, handling business logic, and helping transform prototypes into production-ready systems. My goal is always to deliver solutions that are **simple, efficient, and genuinely useful for the people using them.** Jared Hasson Jared Hasson Full time lead founding dev at a cyber security saas startup, with 10 yoe and a bachelor's in CS. Building & debugging software products is what I've spent my time on for forever

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Frequently Asked Questions

Can SQLite handle a production web application?

SQLite can handle low-to-medium traffic apps (up to a few hundred concurrent users) if configured correctly with WAL mode, busy timeouts, and proper connection management. For high-traffic apps or serverless deployments, PostgreSQL is a better choice.

What is WAL mode and why does it help?

Write-Ahead Logging (WAL) mode changes how SQLite handles concurrent access. Instead of locking the entire database for writes, it writes changes to a separate WAL file. This allows readers to continue reading the old data while a write is in progress, dramatically reducing lock contention.

Related Cursor Issues

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