Introduction

Cloud Firestore is a NoSQL document database designed for seamless scalability, robust performance, and user-friendly app development. Unlike traditional databases, Firestore uniquely describes relationships between data objects, which can be vital for complex applications. Being a part of the Google Cloud platform, it is a powerful successor to Firebase Real-Time Database.

The Firegraph library amplifies the potential of Firestore by allowing efficient retrieval of data across collections, subcollections, and document references.

Primary Goals of Firegraph

• Comprehensive Firestore SDK Coverage: Our future aspirations include supporting real-time updates, caching, and index management through Firestore’s SDK.
• Utilization of GraphQL Syntax: Initially envisioned as a unique query language, Firegraph now embraces standards compliant GraphQL queries for versatility.
• Lightweight Wrapper: Firegraph aims to maintain a minimal footprint while offering support for commonly used Firestore features.

Getting Started with Firegraph

Setting up Firegraph is astonishingly straightforward! You don’t even need a dedicated GraphQL server to get started; however, some GraphQL-related dependencies must be installed.

Installation

# For npm
npm install --save graphql graphql-tag firegraph

# For Yarn
yarn add graphql graphql-tag firegraph

Crafting Queries

You can craft queries directly within your JavaScript files using the gql tag, or leverage the graphql-tag-loader if you’re using webpack to import your GraphQL files directly.

Collections

To illustrate how to query collections, consider the following analogy: Imagine walking through a library where each shelf represents a Firestore collection. Each book on that shelf holds vital information—much like documents in the collection.

const posts = await firegraph.resolve(
  firestore,
  gql`
    query {
      posts {
        id
        title
        body
      }
    }
  `
);

Subcollections

Think of subcollections as books within chapters in your library. Each chapter (document) has its own set of books (subcollection), and querying them involves retrieving data nested within these chapters:

const posts = await firegraph.resolve(
  firestore,
  gql`
    query {
      posts {
        id
        title
        body
        comments {
          id
          body
        }
      }
    }
  `
);

Document References

Picture a map where certain points (document references) lead you to specific locations (documents) in the library: each path (document reference) targets where you will find corresponding information:

const posts = await firegraph.resolve(
  firestore,
  gql`
    query {
      posts {
        id
        title
        body
        author {
          id
          displayName
        }
        comments {
          id
          body
        }
      }
    }
  `
);

Filtering and Ordering Results

Filter results like sorting through a selection of books based on genre, and order them by title or author to find exactly what you need:

const posts = await firegraph.resolve(
  firestore,
  gql`
    query {
      posts(where: { author: $authorId }) {
        id
        title
        author {
          id
          displayName
        }
      }
    }
  `
);

Troubleshooting Ideas

• Ensure that all relevant dependencies are installed correctly.
• Check your Firestore rules and permissions to ensure data accessibility.
• For queries that return no results, verify that your collection and field names match exactly.
• If you encounter performance issues, consider indexing your queries in the Firestore console.

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

Looking Ahead

Our journey with Firegraph is just beginning, with exciting features planned on our roadmap. Joining hands in community contributions accelerates growth, so we encourage you to engage and collaborate!

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.