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Database ⇄ Analytics

Firebase to Treasuredata integration — real-time, two-way sync

Keep Firebase and Treasuredata in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Firebase and Treasuredata

Give Treasuredata the users, events, and records that live in Firebase in real time, and sync the cohorts and scores Treasuredata computes back into Firebase where your applications read them.

A database holds the rows your business runs on: the users, events, orders, and records that every service reads and writes. Treasuredata is where people make sense of them, as dashboards, funnels, cohorts, and metrics. Moving the data from Firebase into Treasuredata usually means a hand-built extract or a change-data-capture pipeline that breaks the moment a column is renamed, and reporting that always trails last night's load.

Stacksync syncs Cloud Storage Objects, Cloud Functions Triggers, Firestore Collections, Firestore Documents in Firebase with Databases, Tables, Master (Parent) Segments, Segments in Treasuredata in real time and in both directions. Operational rows flow into Treasuredata as they change, so dashboards read current data with no pipeline to maintain, and the segments, cohorts, or scores Treasuredata computes flow back into Firebase, where the applications and services that read from it get them at normal query latency. Field-level mapping, schema and type translation, and conflict resolution are handled for you.

Common use cases

  • 01 Write CRM and product-usage records into TD Tables so they become source tables feeding parent-segment unification.
  • 02 Push Predictive Segment propensity scores from TD onto customer records in an operational database or CRM for prioritization and lead routing.
  • 03 Replace one-off Cloud Functions export code with managed, continuous sync.
  • 04 Sync Firestore user and account documents into a CRM so go-to-market teams see live product data.

Common sync patterns

Where Treasuredata tracks product events: behavior onto stored records

Signup, usage, and lifecycle events captured in Treasuredata sync into Firebase as rows, so applications and internal tools can read behavioral data next to the records they already keep.

Where Treasuredata builds cohorts or scores: results your services can read

Segments, cohorts, or scores computed in Treasuredata sync back into Firebase, where the services that read from the database act on them at query speed without calling the analytics API.

Analytics on live operational data, minus the pipeline

The users, events, orders, and records stored in Firebase land in Treasuredata as they change, so dashboards, funnels, and metrics run on current data instead of last night's extract.

What you can sync between Firebase and Treasuredata

Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.

Firebase objects Treasuredata objects How this pairing syncs
Authentication Users User accounts read into CRMs and warehouses for customer records. Journeys Timeline-based event sequences in Audience Studio; stage and membership read out for reporting and cross-system activation. Authentication Users is specific to Firebase and Journeys to Treasuredata — each maps to any object or custom field on the other side.
Cloud Storage Objects Files referenced from documents; usually synced as metadata plus URLs. Predictive Segments AI/ML-scored segments; propensity scores read out and written onto customer records in a CRM or database for prioritization. Cloud Storage Objects is specific to Firebase and Predictive Segments to Treasuredata — each maps to any object or custom field on the other side.
Cloud Functions Triggers Server-side hooks that fire on document changes and can push updates outward. Scheduled Queries Cron-scheduled Presto/Trino (or Hive) jobs that materialize results into result tables; Stacksync reads those materialized tables downstream. Cloud Functions Triggers is specific to Firebase and Scheduled Queries to Treasuredata — each maps to any object or custom field on the other side.
Firestore Collections Top-level groupings of documents that a sync maps to tables or SaaS objects. Query Jobs Ad-hoc Presto/Trino query jobs run asynchronously; results are retrieved from the job result endpoint and fed into downstream systems. Firestore Collections is specific to Firebase and Query Jobs to Treasuredata — each maps to any object or custom field on the other side.
Firestore Documents Schemaless JSON-like records, the primary unit synced to and from external systems. Databases Logical containers for tables; a sync targets one database and maps its tables to warehouse or operational-DB tables. Firestore Documents is specific to Firebase and Databases to Treasuredata — each maps to any object or custom field on the other side.
Subcollections Nested collections under documents, typically flattened into related tables during sync. Tables Columnar log tables in TD's Plazma storage; every row carries a mandatory `time` column (Unix epoch) that Stacksync uses as the incremental watermark and partition key. Synced two-way with warehouse or database tables. Subcollections is specific to Firebase and Tables to Treasuredata — each maps to any object or custom field on the other side.

How changes propagate between Firebase and Treasuredata

Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.

Firebase Treasuredata Interval-based propagation

DetectionStacksync polls Firebase for changes on an incremental schedule, reading only records changed since the previous pass. Real-time snapshot listeners on Firestore queries and Cloud Functions triggers on document changes.

DeliveryEach detected change is written to Treasuredata through its API, with automatic retries and rate-limit backoff.

Treasuredata Firebase Interval-based propagation

DetectionStacksync polls Treasuredata for changes on an incremental schedule, reading only records changed since the previous pass. Polling on the mandatory `time` column (Unix-epoch partition key) or an updated-at column.

DeliveryEach detected change is written to Firebase through its API, with automatic retries and rate-limit backoff.

Rate-limit considerations

  • Firebase: Subject to Firestore's documented operation quotas and per-document write throughput limits.
  • Treasuredata: TD does not publish a fixed request-per-second cap; query throughput is bounded by the account's compute resource pool and large reads/exports run as asynchronous jobs.
What ships with Firebase ⇄ Treasuredata

Connect Firebase and Treasuredata for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Firebase–Treasuredata connection.

Real-time

Two-way sync

Changes in Firebase or Treasuredata instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Firebase or Treasuredata data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.

At scale

Event queues

Handle millions of events per minute without losing a single Firebase or Treasuredata record.

Observability

Monitoring

Track your Firebase ⇄ Treasuredata sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Firebase and Treasuredata.

How the Firebase and Treasuredata connectors work

Firebase

Integration surface
REST and gRPC APIs, typically accessed through the Firebase Admin SDK
Authentication
Google service account credentials (IAM) for server-side access; Firebase Auth tokens for client contexts
Change detection
Real-time snapshot listeners on Firestore queries and Cloud Functions triggers on document changes
Capabilities
read · write
Rate limits
Subject to Firestore's documented operation quotas and per-document write throughput limits

Treasuredata

Integration surface
TD API v3 (REST) for databases, tables, and jobs, plus the Audience API (REST) for CDP segments and journeys
Authentication
API key sent as an `Authorization: TD1 <api_key>` header (per-user or account key from the TD Console); requests go to the region-specific endpoint (e.g. api.treasuredata.com for US, with separate EU and Tokyo endpoints)
Change detection
Polling on the mandatory `time` column (Unix-epoch partition key) or an updated-at column; TD stores append-oriented columnar data with no per-row CDC stream, so incremental syncs query for rows past a stored watermark
Capabilities
read · write
Rate limits
TD does not publish a fixed request-per-second cap; query throughput is bounded by the account's compute resource pool and large reads/exports run as asynchronous jobs
How it works

How to connect Firebase to Treasuredata — three steps, no code

Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.

  1. 01

    Connect your apps

    Authenticate Firebase and Treasuredata with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Firebase connected
    Treasuredata connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Firebase and Treasuredata objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Firebase ⇄ Treasuredata
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Firebase Treasuredata
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Firebase and Treasuredata integration FAQ

SECURITY

Security teams trust Stacksync

As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.

Learn more about security
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS

SSO & SCIM

Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.

Alerts

Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.

Secure connection options

Securely connects to your systems with:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 406 integrations available for Firebase and Treasuredata.

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