Firebase Realtime Database

Google Firebase is a Google-backed application development software that enables developers to develop Android, iOS, and Web apps. Firebase provides features like analytics, reporting and fixing app crashes, creating marketing and product experiments, and also provide real-time database.

Why go for Firebase Realtime database?

The Firebase real-time database is a cloud-hosted and simple JSON formatted NoSQL database that enables data to be stored in single-rooted JSON format and synced between users in real-time. The data is synced across all clients in real-time and is still available when an app goes offline.

To create HTTP requests and response service APIs, we need to do a lot of configuration, and we also need knowledge of backend services. Also to synchronize our local database to the server is a difficult task for developers. Instead of typical HTTP requests, the firebase data indexing in realtime provides event-based data synchronization. Every time data changes, all connected device receives that update within milliseconds. The data change events are invoked with all connected devices and provide updated data. The data change events are invoked with all connected devices, and provide updated data.

Maintaining offline data is also very simple in firebase because firebase apps remain responsive even when offline. The Firebase Realtime Database SDK persists your data to disk. Once connectivity is reestablished, the client device receives any changes it missed, synchronizing it with the current server state.

The firebase data indexing in realtime can be accessed directly from a mobile device or web browser. There’s no need for an application server. Security and data validation are available through the Firebase Realtime Database Security Rules, expression-based rules that are executed when data is read or written.

Firebase provides the best solutions for mobile app development. Firebase Real-Time database is one of the good features of that. But it has its own advantages and limitations also.

As we know, Firebase real-time data fetch listeners work fine with a small amount of data, but as data increases the performance of data read is also decreases.

In this blog, we are going to discuss the indexing of the firebase data fields and values to increase the performance of the firebase query. Indexing increases the performance of orderByChild() and orderByValue() queries.

A node’s key is indexed automatically, so there is no need to index it explicitly. Firebase supports indexing by field names and field values.

Explicit indexing is added in the section of the Rules tab of the Real-Time database.

Indexing with orderByValue:

To demonstrate how .indexOn works with orderByValue(), Suppose we have a database structure of cricket players World Cup runs like,

{
"scores": {
"ViratKholi" :557,
"MSDhoni" : 346,
"RohitSharma" : 746,
"ShikharDhawan" : 256,
"KLRahul" : 545,
"RPant" : 228
}

}

We’re using orderByValue() to get players sorted by scores of World Cup OR top scorers by .orderByValue() followed by .limitToFirst(). We can optimize our queries by adding a .value rule on our /scores node:

{
  "rules": {
    "scores": {
      ".indexOn": ".value"
    }
  }
}

Indexing with orderByChild:

We will use the following Database structure to explain how .indexOn works with orderByChild().

"employee":{
  "employee1": {
    "empName" :Rohit Sharma,
    "branchName" : Noida,
    "Designation" : SW Developer,
    "empId" : EMP776,
    "salary": {
     "basic" :20000,
     "HA" : 5000,
     "PF" : 2500,
     "OA" : 2500,
     "total" : 30000, 
   }
  },
"employee2": {
    "empName" :Virat Kholi,
    "branchName" : Dheli,
    "Designation" : SW Developer,
    "empId" : EMP908,
    "salary": {
    "basic" :25000,
    "HA" : 5000,
    "PF" : 5000,
    "OA" : 5000,
    "total" : 40000, 
   }
  }
}

Now, if you want to order the data by empName, empId, and designation you need to update rules as follows,

{
  "rules": {
    "employee": {
      ".indexOn": ["empName", "empId", "designation"]
    }
  }
}

You can add indexing on any level of data as other rules. If you want to add indexing on empName, empId which is on the first level, and basic, total which is on the second level of employee data structure, you need to update rules as follows,

{
  "rules": {
    "employee": {
      ".indexOn": ["empName", "empId","salary/basic", "salary/total"]
    }
  }
}

There is another way to specify multilevel indexing as,

{
  "rules": {
    "employee": {
       ".indexOn": ["empName", "empId", "designation"],
     "$key": {
      "salary": {
       ".indexOn": ["basic", "total"]
     }
     }
     }
   }
}

You can create indexing on any of your node with a comma separating as,

{
  "rules": {
    "employee": {
      ".indexOn": ["empName", "empId","salary/basic", "salary/total"]
    },
  "scores": {
      ".indexOn": ".value"
    }
  }
}