PipeKeelBeta

NoSQL

MongoDB and Firestore into BigQuery — and results back

PipeKeel reads MongoDB collections (Atlas, self-hosted, Amazon DocumentDB, Azure Cosmos DB for MongoDB) and Firestore collections or collection groups, turns each document into a row — nested fields as columns, lists into rows with Unnest array — and loads them into BigQuery, Google Sheets, a database or PipeKeel storage on a schedule, reading only new or changed documents. Results such as customer stats can be written back as documents.

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How it works

  1. Connect the database

    MongoDB: the Atlas cluster address and a read-only user. Firestore: a service-account key.

  2. Pick a collection

    With an optional filter; PipeKeel finds the fields from a sample of documents.

  3. Shape the documents

    Nested fields are already columns; Unnest array turns an order's items into rows.

  4. Load and schedule

    Into BigQuery (merged on the document id), Sheets or a database — or back into MongoDB or Firestore.

What you get

  • Atlas mongodb+srv addresses, replica sets and TLS with your provider's CA
  • Firestore subcollections and collection groups
  • Only new or changed documents, by a field such as updatedAt
  • Insert, upsert or merge documents back, with nested objects and lists
  • Templates: sync to BigQuery, daily revenue, active users, customer stats

Questions

How are nested documents handled?

Nested objects become columns such as customer_address_city (up to three levels deep); lists stay JSON, and the Unnest array block turns them into one row per item.

Can PipeKeel write to MongoDB or Firestore?

Yes — insert, replace or upsert MongoDB documents by key, and add, replace or merge Firestore documents by id.

Start with the Team plan, free for 14 days

Then keep a free plan, or choose a paid one. No credit card.

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