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

Keep Datadog and Firebase 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 Datadog and Firebase

Keep Firebase and Datadog in step: the rows in your database and the Monitors, Logs, Events, Dashboards your engineering tools track stay consistent in real time, in both directions.

Firebase is where your application's durable data lives; Datadog is where engineering and operations teams track the issues, events, messages, or identities that run alongside it. The two overlap constantly, a row should open a ticket, an alert should land as a record, a user in one should exist in the other, but bridging them today means per-tool integration code: auth, webhooks, pagination, rate limits, and retries, built and maintained separately for every tool.

Stacksync syncs Authentication Users, Cloud Storage Objects, Cloud Functions Triggers, Firestore Collections in Firebase with Monitors, Logs, Events, Dashboards in Datadog field by field, in real time, and in both directions. You decide which system owns which fields; Stacksync keeps every copy consistent and resolves conflicts by rules you set, so the database and the tooling around it never drift apart.

Common use cases

  • 01 Write CRM-side changes (plan, status, owner) back into Firestore documents the app reads.
  • 02 Combine Firebase Authentication users with billing and CRM records into one customer table.
  • 03 Load Events and Incidents into a warehouse to correlate deploys, alerts, and outages on one timeline for post-incident review.
  • 04 Pull the Hosts inventory into a CMDB or database for asset tracking, tag hygiene, and cost allocation across teams.

Common sync patterns

React to changes on either side in near real time

Updates in Datadog arrive as row changes in Firebase, and writes to Firebase propagate to Datadog within seconds, so triggers, jobs, and alerts fire without polling.

Where Datadog manages users or groups: keep identity aligned

Directory and identity records in Datadog stay matched to the users or owners table in Firebase, so provisioning and de-provisioning flow from one source.

Turn rows into the records your tools track

A new or changed row in Firebase creates or updates the matching record in Datadog, whether that is an issue, an event, a message, or a user, so the tool reflects the database without a custom API job.

What you can sync between Datadog and Firebase

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.

Datadog objects Firebase objects How this pairing syncs
Metrics Time-series metrics queried in aggregate windows through the query API and submitted via POST /api/v1/series; individual raw points cannot be extracted beyond retention. Authentication Users User accounts read into CRMs and warehouses for customer records. Metrics is specific to Datadog and Authentication Users to Firebase — each maps to any object or custom field on the other side.
Incidents Incident records from the v2 Incidents API with full CRUD, including status and timeline fields; landed in a database for MTTR reporting or created and updated from an external incident workflow. Cloud Storage Objects Files referenced from documents; usually synced as metadata plus URLs. Incidents is specific to Datadog and Cloud Storage Objects to Firebase — each maps to any object or custom field on the other side.
Service Level Objectives SLO definitions and status history via the v1 SLO API with full CRUD; read out for reliability and error-budget reporting, or provisioned and updated from a reliability config. Cloud Functions Triggers Server-side hooks that fire on document changes and can push updates outward. Service Level Objectives is specific to Datadog and Cloud Functions Triggers to Firebase — each maps to any object or custom field on the other side.
Hosts Infrastructure host inventory with tags and metadata from the v1 host list API; loaded into a CMDB or warehouse for asset tracking, and hosts can be muted or unmuted via the API. Firestore Collections Top-level groupings of documents that a sync maps to tables or SaaS objects. Hosts is specific to Datadog and Firestore Collections to Firebase — each maps to any object or custom field on the other side.
Monitors Alert definitions with query, thresholds, and current state via the v1 Monitors API, which supports full create, update, and delete; Stacksync reads alert state into a warehouse or provisions and updates monitors from a config source. Firestore Documents Schemaless JSON-like records, the primary unit synced to and from external systems. Monitors is specific to Datadog and Firestore Documents to Firebase — each maps to any object or custom field on the other side.
Logs Log events searched via the v2 Logs search endpoint by time window and submittable through the log intake API; commonly streamed to a warehouse for retention beyond Datadog's storage period. Subcollections Nested collections under documents, typically flattened into related tables during sync. Logs is specific to Datadog and Subcollections to Firebase — each maps to any object or custom field on the other side.

How changes propagate between Datadog and Firebase

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.

Datadog Firebase Sub-second propagation

DetectionDatadog notifies Stacksync of record changes through webhook events. Polling with time-windowed search queries on Logs and Events (timestamp cursor).

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

Firebase Datadog 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 Datadog through its API, with automatic retries and rate-limit backoff.

Rate-limit considerations

  • Datadog: Per-endpoint limits return HTTP 429 with X-RateLimit-Limit/-Remaining/-Period/-Reset headers. Log ingestion and metric submission are not rate limited; search endpoints such as Logs and Events queries carry quotas that Datadog Support can raise.
  • Firebase: Subject to Firestore's documented operation quotas and per-document write throughput limits.
What ships with Datadog ⇄ Firebase

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Datadog or Firebase 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 Datadog or Firebase record.

Observability

Monitoring

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

Trading partners

EDI

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

How the Datadog and Firebase connectors work

Datadog

Integration surface
REST API (v1 and v2)
Authentication
API key (DD-API-KEY) plus an Application key (DD-APPLICATION-KEY) sent as request headers; application keys are tied to the creating user and inherit that user's permissions and authorization scopes.
Change detection
Polling with time-windowed search queries on Logs and Events (timestamp cursor); monitor alerts can also push via the Webhooks notification integration. No modified-date CDC on mutable objects.
Capabilities
read · write · webhooks
Rate limits
Per-endpoint limits return HTTP 429 with X-RateLimit-Limit/-Remaining/-Period/-Reset headers. Log ingestion and metric submission are not rate limited; search endpoints such as Logs and Events queries carry quotas that Datadog Support can raise.

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
How it works

How to connect Datadog to Firebase — 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 Datadog and Firebase 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
    Datadog connected
    Firebase connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Datadog and Firebase 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 · Datadog ⇄ Firebase
    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
    Datadog Firebase
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Datadog and Firebase 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 411 integrations available for Datadog and Firebase.

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