Bubble vs GitHub Spark

⚠ Watch out for

• Vendor lock-in is a significant concern. Once you build your app on Bubble, you're tied to their cloud infrastructure. There's no way to export your code or migrate to another platform without rebuilding from scratch. This is a major risk for businesses that may need to scale or move to a custom solution later, as it can lead to substantial rework costs.
• Performance can be a bottleneck under heavy load. Bubble's cloud environment is not designed for high-concurrency, data-intensive applications. If your AI app experiences a spike in users, you might encounter slower response times or throttling. This is a critical limitation for production-scale deployments, as it can harm user experience and deter growth.
• The no-code approach limits advanced customization. While the visual builder is powerful, it's constrained by Bubble's pre-built components and logic. If you need to implement complex business logic or leverage cutting-edge AI models with custom parameters, you'll hit walls. There's no direct code generation, so you can't tweak the underlying code to overcome these constraints.
• Support is a mixed bag. While there's a robust knowledge base and community forums, direct support (email/chat) is only available on higher plans. On the free tier or Basic plan, you may have to rely on community help, which can be slow or inconsistent. For a platform where you're building business-critical apps, this can be frustrating.
• The learning curve is steeper than expected for a no-code tool. Despite the AI Copilot, understanding Bubble's data model, workflows, and plugin ecosystem takes time. New users often find themselves watching tutorials and reading documentation for weeks before becoming proficient, which contradicts the 'instant' no-code promise.