Firebase Studio by Google: Is it Better than Cursor or Windsurf?

Vipin Vashisth Last Updated : 23 Apr, 2025
8 min read

Think of Firebase Studio as your co-pilot in the cloud. It’s a smart, agentic workspace where building, testing, and launching apps feels less like a chore and more like a creative flow. Whether you’re sketching your next big idea or fine-tuning a real-time database, Firebase (by Google) shows up as a reliable, intuitive partner. Interestingly, Firebase wasn’t always part of the Google universe. It was acquired by Google in 2014 and has since evolved into a core pillar of the Google Cloud ecosystem.

A common question among developers: Is Firebase free?
The answer: Yes, up to a point.

It offers a generous free tier with usage-based upgrades as your app scales. This article explores Firebase’s capabilities and limitations and compares it with top Firebase alternatives like Windsurf and Cursor AI, which focus more on AI-assisted coding.

What is Firebase?

Firebase Studio is a cloud-based development environment launched by Google, designed to streamline the process of building, testing, deploying, and managing full-stack applications, particularly those incorporating artificial intelligence. It operates entirely within a web browser, eliminating the need for complex local setups and allowing access from any device with an internet connection.

Key Aspects of Firebase Studio

  • Simplify coding workflows: Create and test code with Gemini’s assistance integrated throughout Firebase. Easily handle common development tasks, including debugging, testing, refactoring, explaining, and documenting your code.
  • Enhance existing apps: Bring in codebases from your local machine or repositories (GitHub, GitLab, Bitbucket). Design and share team-wide templates for your preferred technology stacks.
  • Create full-stack experiences: Develop and modify all application components, from AI models, agents, and RAG systems to user interfaces, business logic, and databases. Seamlessly incorporate tools like APIs and microservices into your AI applications.
  • Work with familiar tools: To customize your workspace, import your specific configurations, including system tools, extensions, and environment variables. Then, access a vast library of extensions from the Open VSX Registry.
  • Flexible deployment options: You can launch your application in the cloud using built-in Firebase backend services and Google Cloud Run integrations or deploy it on your infrastructure.

Firebase Studio is currently available in preview. It offers users three free workspaces, with options to expand this number through Google Developer Program membership. While the base service is free, using certain integrated services like Firebase App Hosting or exceeding free quotas for the Gemini API may require a Cloud Billing account and incur costs.

How to Access Firebase?

Time needed: 2 minutes

To access Google Firebase Studio, follow these steps:

  1. Go to the Firebase console

    Visit Firebase Studio. Scroll a little down and click on “Try Firebase Studio now.”

  2. Create or select a project

    If you’re new to Firebase, you’ll need to create a project. If you have existing projects, select one from your dashboard. Firebase Studio by Google - sign in

  3. Navigate the Firebase console

    Once in your project, you’ll see the Firebase console (sometimes called Firebase Studio) with navigation options on the left sidebar for various Firebase services:

    – Authentication
    – Firestore Database
    – Realtime Database
    – Storage
    – Hosting
    – Functions
    – Machine LearningNavigate the Firebase console

  4. Set up your project

    Follow the setup instructions for each service you want to use.Set up your project

  5. Connect your app

    Use the Firebase SDK for your platform (Web, iOS, Android) by following the provided configuration instructions in the console.Connect your app

For further guidance on getting started with Firebase Studio, refer to the official documentation.

Firebase Studio in Action

Now, we’ll explore three core areas where Firebase Studio can greatly boost development efficiency:

  • Building a SpendWise App
  • Building a MapMinds App
  • ML Application

Through the power of its inbuilt features and AI, developers can automate workflows, reduce setup time, and concentrate on developing scalable, smart apps. Let’s discuss each area in detail.

Task 1: Building a SpendWise App

Prompt: “A budgeting and expense tracking app with customizable spending categories, detailed charts, and budget goals. The app allows users to categorize their expenses from necessities to lifestyle choices, offering a clear overview of their financial habits. It provides interactive graphs and pie charts to break down spending patterns and helps set monthly budget goals with easy tracking

Task Review

The SpendWise app built with Firebase Studio performs well in generating a functional budgeting tool with minimal manual input. It effectively categorizes expenses, sets budget goals, and provides clear visualizations (bar, line, pie charts) with filters for day, week, and month. A key strength is its ability to auto-correct initial errors, streamlining development. However, it could improve in areas like UI customization, performance optimization for large datasets, and adding features like recurring expenses or income tracking for a more complete budgeting experience.

Task 2: Building a MapMinds App

Prompt: “An App That Turns a Theme or Topic Into a Mindmap

Task Review

The MapMinds app built with Firebase Studio struggles to deliver its core functionality. Instead of a clear mind map, it displays related concepts in a flat circular layout, lacking structure and depth. The UI is also poorly designed, making interaction difficult. Overall, it needs major improvements in both logic and visual presentation to serve its purpose effectively.

Task 3: ML Application

Prompt: “Build a Machine Learning model that will classify whether a person have diabetes or not.

Task Review

The ML application built with Firebase Studio has a decent UI, offering a clean and user-friendly interface. However, its core functionality of predicting diabetes risk is unreliable. The model outputs inconsistent and seemingly random risk percentages for the same input data, indicating issues with model training or integration. While the design is solid, the prediction logic needs significant improvement for the app to be trustworthy and usable in real scenarios.

Overall Analysis

Firebase Studio performs well for simple, structured apps like SpendWise. It created a functional budgeting tool with clear charts and reliable data handling. The platform fixed initial errors automatically, showing strong low-code support. UI and filters worked smoothly. For straightforward use cases, Firebase Studio is efficient and user-friendly.

However, it struggles with complex logic in apps like MapMinds and ML Applications. MapMinds lacked a proper mind map structure and had poor UI. The ML app gave random predictions, making it unreliable. These tasks exposed limitations in handling visual complexity and model integration.

Project IDX Meets Firebase Studio

Google has moved Project IDX from experiment to product by integrating it into Firebase Studio. This change follows developer feedback showing that combining IDX with Firebase and AI advances creates the best development platform. All existing IDX features remain available to users.

The transition keeps all core functionality intact. Users can still access cloud development environments, framework templates, application imports, web previews, Android emulators, and Google API integrations.

Firebase Studio brings several important improvements:

  • Streamlined AI tools: Gemini features now work seamlessly with Firebase Gemini models for better coding assistance
  • Better prompting options: Support for text, images, and drawing tools, plus an App Prototyping agent for building full-stack apps
  • Firebase service connections: Direct publishing to Firebase App Hosting and AI flow creation with Genkit
  • Faster performance: Quicker load times, faster builds, and improved responsiveness
  • More customization: Additional options for personalizing your development workspace

Users need to accept the new Terms of Service when they next log in to access their projects.

Key Applications of Firebase

Firebase is a comprehensive platform that can be utilized across many applications within mobile and web development. Its built-in collection of tools aids developers in developing, running, and scaling applications effectively. Principal applications and areas of use comprise:

  • Cloud-Based Development: Access a fully-featured development environment from any device, with seamless syncing and deployment capabilities.
  • AI-Powered Coding Assistance: Leverage Gemini models integrated into Firebase for intelligent code suggestions, multimodal prompting, and rapid app prototyping using tools like the App Prototyping agent.
  • Flexible Project Integration: Import existing repositories and customize your workspace to fit your tech stack and workflow.
  • Framework & Language Support: Build using popular languages and frameworks such as Go, Java, .NET, Python, Android, Flutter, and web technologies like React, Angular, and Vue.js.
  • Built-in Testing Tools: Utilize built-in emulators, testing suites, and debugging tools to streamline development and quality assurance.
  • Real-Time Collaboration: Collaborate with team members in real-time, sharing code, previews, and workflows instantly.
  • Deep Firebase Integration: Easily connect with Firebase services for hosting, databases, analytics, AI workflows, and RAG-based systems with Genkit.

Future Implications

Firebase Studio provides a robust cloud environment with AI support and easy Firebase integration. However, inconsistent code generation, limited debugging, and shallow framework support hold it back. To boost reliability and make it fit for production-ready AI apps, future upgrades could include:

Robust AI Code Generation & Debugging

  • Current Challenge: AI-generated code is inconsistent, sometimes functional, and sometimes error-prone.
  • Future Focus: Improve Gemini’s contextual understanding and debugging capabilities. Integrate real-time linting, error diagnosis, and auto-fix suggestions for more production-ready code.

Reliable Multimodal Prototyping

  • Current Challenge: While App Prototyping with natural language and images is promising, it often lacks reliability in full-stack deployment.
  • Future Focus: Enhance multimodal prompt interpretation by better aligning visual input (drawings/UI mockups) and generated code structures.

Stronger Framework-Specific Tooling

  • Current Challenge: Generic support exists for frameworks like React or Flutter but lacks deep integrations (e.g., project scaffolding, routing, component reuse).
  • Future Focus: Provide framework-aware templates, contextual AI suggestions, and smarter code snippets tailored to the selected tech stack.

Consistent Deployment Pipeline

  • Current Challenge: Users experience broken builds or unclear errors during deployment to Firebase Hosting.
  • Future Focus: Offer clear build logs, automated fixes, and guided deployment pipelines with fallback options or test environments.

Collaboration and Version Control

  • Current Challenge: Real-time collaboration is in the early stages; it lacks advanced team workflows.
  • Future Focus: Enable live code reviews, pair programming, and integrated Git workflows for collaborative builds.

Firebase vs Cursor vs Windsurf

In this section, we compare Firebase, Windsurf, and Cursor AI. These tools support backend development and AI-assisted coding, each offering unique strengths for modern developers.

Feature Firebase Windsurf Cursor AI
Use Case Backend-as-a-Service for real-time apps AI code editor with proactive coding support AI code editor with natural language-based code generation
Strengths Realtime DB, Auth, HostingScales wellGood for fast prototyping Deep codebase understandingSmart code suggestionsWorks well in VS Code Natural language to codeProject-wide contextStrong integration with VS Code
Weaknesses Not great for complex logic/MLLimited visual logic support Limited IDE supportNeeds iterations for complex code Slower on large codebasesNeeds context setup for multi-file tasks
UI/UX Clean for basic apps Modern, productivity-focused Clean and collaborative
Collaboration Basic user handling via Auth Limited for teams Strong, especially in the Pro plan
Ideal For Fast MVPs, real-time tools Devs needing proactive coding help Devs prefer AI pair programming in VS Code
Pricing Free tier + usage-based Free + Pro ($15/mo) Free + Pro ($20/mo)

Also Read: Is Vibe Coding the Future? See What Top Leaders Have to Say!

Conclusion

Firebase, Cursor AI, and Windsurf support different parts of the development process. Firebase is strong in backend development. It offers real-time databases, hosting, and fast deployment, making it ideal for building MVPs and scalable apps. Tasks like SpendWise showed Firebase’s strength in the backend and smooth UI handling.

On the other hand, Cursor AI and Windsurf focus on coding help. They work inside code editors like VS Code. Cursor helps turn natural language into code. Windsurf gives smart suggestions and understands large codebases. Firebase is not a better version of these tools. It complements them by handling the backend, not coding assistance.

Frequently Asked Questions

Q1. Can Firebase replace Cursor AI or Windsurf?

A. No, Firebase is focused on backend services, while Cursor AI and Windsurf are designed for AI-assisted coding. They serve different purposes and are best used together.

Q2. Which is better for building complete apps: Firebase, Cursor AI, or Windsurf?

A. Firebase is better for building and deploying complete apps, especially with real-time data and backend needs. Cursor AI and Windsurf are better for writing and improving code efficiently.

Q3. Is Firebase suitable for machine learning tasks?

A. Firebase is not ideal for complex ML tasks. It can store and serve models but lacks native ML tools. ML tasks are better handled in dedicated environments like TensorFlow or PyTorch.

Q4. Which tool is more beginner-friendly?

A. Firebase is beginner-friendly for app development. Cursor AI is easy to use for coding with natural language. Windsurf may need some code familiarity to get the most out of it.

Q5. Can Cursor AI or Windsurf deploy apps like Firebase?

A. No, Cursor AI and Windsurf assist with code writing but don’t offer hosting or backend services. Firebase handles deployment, database, and authentication.

Hi, I'm Vipin. I'm passionate about data science and machine learning. I have experience in analyzing data, building models, and solving real-world problems. I aim to use data to create practical solutions and keep learning in the fields of Data Science, Machine Learning, and NLP. 

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