> ## Documentation Index
> Fetch the complete documentation index at: https://docs.condense.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Firebase Firestore (Output, Stream)

**Connector Type:** Output Connector

**Description**

Streams processed data from Condense into Firebase Firestore for real-time storage, downstream analytics, and cloud-native integrations.

**Brief Description**

The Firebase Firestore Stream Output Connector enables Condense to publish messages from Kafka-native topics into Google Firebase Firestore collections. It authenticates using a Google Cloud Service Account, transforms incoming Kafka messages into Firestore documents, and writes them using configurable write modes and batch sizes.

This connector is ideal for real-time application backends, user profile storage, IoT telemetry, mobile applications, and event-driven architectures built on Firebase.

**Links to Relevant Documents**

* [https://firebase.google.com/docs/firestore](https://firebase.google.com/docs/firestore)
* [https://cloud.google.com/firestore/docs/reference/rest](https://cloud.google.com/firestore/docs/reference/rest)
* [https://cloud.google.com/iam/docs/service-accounts](https://cloud.google.com/iam/docs/service-accounts)

**Connector Overview**

The Firebase Firestore Stream Output Connector integrates Condense with Google Firestore, enabling continuous streaming of processed events into Firestore collections.

Common use cases include:

A. Persisting application events.

B. IoT telemetry storage.

C. Mobile and web application backends.

D. Event-driven microservices using Firebase.

**Core Functionality**

1. Consumes messages from Kafka-native Condense topics.
2. Writes documents into Firestore collections.
3. Supports Insert, Update, and Upsert write modes.
4. Performs configurable batch writes for improved throughput.
5. Authenticates securely using Google Cloud Service Accounts.

**How It Works in Condense**

1. The connector subscribes to the configured Kafka-native topic.
2. It authenticates using the provided Google Cloud Service Account.
3. Incoming messages are converted into Firestore document format.
4. Documents are written into the configured Firestore collection.
5. Depending on the selected write mode, documents are inserted, updated, or upserted.

**Configuration**

| **Category**   | **Field Name**      | **Description**                    | **Required** |
| :------------- | :------------------ | :--------------------------------- | :----------: |
| General        | Title               | Unique connector name              |      Yes     |
| Firebase       | Firebase Project ID | Firebase project identifier        |      Yes     |
| Authentication | Service Account Key | Google Cloud Service Account JSON  |      Yes     |
| Firestore      | Collection Path     | Destination Firestore collection   |      Yes     |
| Firestore      | Write Mode          | Insert, Update, or Upsert          |      Yes     |
| Performance    | Batch Write Size    | Number of documents per batch      |      No      |
| Condense       | Topic (Input)       | Kafka-native topic to consume from |      Yes     |

**Field-by-Field Explanation**

**1. Title**

Unique identifier for the connector.

**Example:**

`Firestore_Output_Connector`

**2. Firebase Project ID**

Identifier of the Firebase project hosting Firestore.

**Example:**

`my-firebase-project`

**3. Service Account Key**

JSON credentials for a Google Cloud Service Account with Firestore write permissions.

Generate the key from:

**Firebase Console → Project Settings → Service Accounts**

**4. Firestore Collection Path**

Destination collection where documents will be stored.

**Examples:**

* telemetry\_data
* fleet/vehicle\_logs

**5. Write Mode**

Determines how documents are written.

Supported values:

* Insert
* Update
* Upsert

Choose the mode that best matches your application requirements.

**6. Batch Write Size**

Number of records grouped into a single Firestore write operation.

**Default:**

`100`

Larger batch sizes improve throughput but should remain within Firestore limits.

**7. Topic (Input)**

Kafka-native Condense topic from which records are consumed.

**Example:**

`vehicle_data_stream`

**Sample Configuration Example**

```json theme={null}
{
  "title": "Firestore_Output_Connector",
  "firebaseProjectId": "my-firebase-project",
  "serviceAccountKey": "{...}",
  "firestoreCollectionPath": "fleet/vehicle_logs",
  "writeMode": "upsert",
  "batchWriteSize": 100,
  "inputTopic": "vehicle_data_stream"
}
```

**Troubleshooting and Common Issues**

**1. No Documents Written**

**Cause:** Connector is not running or the configured topic has no messages.

**Solution:** Verify connector status and confirm messages are available in the configured Kafka-native topic.

**2. Permission Denied**

**Cause:** Service Account lacks Firestore write permissions.

**Solution:** Assign the required Firestore IAM roles and verify the Service Account credentials.

**3. Invalid Collection Path**

**Cause:** Incorrect collection path syntax.

**Solution:** Verify the configured Firestore collection path.

**4. Partial Batch Failures**

**Cause:** Invalid document payloads or schema issues.

**Solution:** Review connector logs to identify failed records and correct the payload before retrying.

**Advanced Topics**

**1. Document ID Mapping**

Documents can use a field from the incoming message as the Firestore document ID or allow Firestore to generate document IDs automatically.

**2. Batch Writes**

Batch operations improve write throughput while reducing network overhead.

Configure batch sizes based on expected event volume and Firestore limits.

**3. Retry Handling**

Transient failures such as network interruptions or quota throttling are automatically retried according to Condense retry policies.

**4. Payload Requirements**

Incoming records should be valid JSON documents.

Binary or non-JSON formats should be transformed before reaching this connector.

**Best Practices**

1. Use dedicated Firestore collections for different business domains.
2. Use least-privilege Service Accounts for authentication.
3. Rotate Service Account credentials periodically.
4. Test connector configurations with small batch sizes before deploying to production.
5. Monitor connector logs and Firestore quotas to ensure reliable streaming.