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Firetable

Firetable is a spreadsheet-like UI for Firestore.

No more building admin portals to let business users to access data from Google Cloud.

Firetable UI

Supports fields such as images, files, single/multi select, in addition to standard fields. Functions such as row resizing, data import/export are supported. More coming soon, for comprehensive list see ROADMAP.md.

Firetable screenshot

Setup instructions

1. Create a Firebase project (Instructions)

  • Enable the Firestore database
  • Set up Firestore Security Rules: use Test Mode or set up required permissions. Below are sample rules that allow for unlimited access to the entire database:
    rules_version = '2';
    service cloud.firestore {
      match /databases/{database}/documents {
        match /{document=**} {
          allow read, write: if true;
        }
      }
    }
    
  • Upgrade project to the Blaze Plan
  • Enable the Google sign-in method in Authentication / Sign-in method

2. Create an Algolia project

  • Get the generated Application ID and Search-Only API Key from the API Keys page

3. Clone this repo

git clone https://github.com/AntlerVC/firetable.git

4. Set up Cloud Functions

  • Install dependencies
cd cloud_functions/functions
yarn
  • Ensure that you have Firebase CLI installed. (Instructions)

  • Set cloud environment keys for Algolia

firebase functions:config:set algolia.appid=YOUR_APP_ID algolia.apikey=ADMIN_API_KEY
  • Deploy the Cloud Functions to your Firebase project
yarn deploy

5. Set React app environment variables

Create a .env file in the www directory

  • Get the generated Application ID and Search-Only API Key from the Algolia API Keys page

  • Get the Firebase Project ID and Web API Key from your Firebase Project’s Settings page. Click the cog icon on the left sidebar (under the Firebase logo) and click Project settings

REACT_APP_ALGOLIA_APP_ID=
REACT_APP_ALGOLIA_SEARCH_API_KEY=

REACT_APP_FIREBASE_PROJECT_ID=
REACT_APP_FIREBASE_PROJECT_WEB_API_KEY=

6. Install front-end dependencies

cd www
yarn

7. Run project locally

yarn start