See why hundreds of industry leaders trust Secoda to unlock their data's full potential.
See why hundreds of industry leaders trust Secoda to unlock their data's full potential.
Get the guideThe integration of Firestore and BigQuery is primarily aimed at enhancing data analysis and reporting. Firestore, being a serverless document database, is excellent for storing, updating, and querying documents. However, for analytic reporting, BigQuery is more efficient. The integration allows automatic replication of inserts, updates, and deletes in Firestore to BigQuery, thus improving data accessibility and analysis.
There are two primary methods to load data from Firestore to BigQuery. The first approach involves exporting Firestore data to Google Cloud storage and then importing it to BigQuery. The second approach is to stream data directly from Firestore to BigQuery, which can be achieved using the “Export Collections to BigQuery” Firebase extension.
The “Export Collections to BigQuery” Firebase extension works by exporting the documents in a Cloud Firestore collection to BigQuery in real-time and incrementally. It scans for changes in the document collection and automatically sends the action (document creation, deletion, or update) to BigQuery. This allows for real-time data analysis and reporting.
// Initialize the Firebase extension
const exportCollectionsToBigQuery = require('firebase-export-collections-to-bigquery');
// Use the extension
exportCollectionsToBigQuery.start({
collections: ['collection1', 'collection2']
});
Integrating Secoda with BigQuery provides users with enhanced data discovery and management capabilities. This integration allows users to easily find tables and metadata, and understand how BigQuery tables connect with other data. Furthermore, Secoda can be utilized to swiftly discover, classify, and profile datasets, and establish data quality using BigQuery.
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