Real-time
Two-way sync
Changes in Dremio or Firebase instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ Database
Dremio to Firebase integration — real-time, two-way sync
Keep Dremio 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.
- SOC 2 and 6 other compliance frameworks
- POC with real engineers in minutes
Adopted by fast-scaling companies moving mission-critical data in real time
Case study
Migrated from Mulesoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Dremio and Firebase
Connect Firebase and Dremio with one live, two-way sync: operational rows flow into the warehouse, and computed results flow back where systems can read them fast.
Operational databases and analytical warehouses want the same data at different moments. Analysts want Firebase's rows in Dremio, current and joinable, without a change-data-capture pipeline to maintain. Engineers want the outputs of warehouse work, such as aggregates, features, and segments, available in Firebase where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in Firebase sync into Dremio in real time, and result tables in Dremio sync back into Firebase, with schema and type mapping between the two systems handled for you.
Common use cases
- Reverse-ETL aggregates computed over lake data out to CRMs and finance tools for business users.
- Publish operational database tables into Iceberg via Dremio so the lakehouse reflects current application state.
- Replace one-off Cloud Functions export code with managed, continuous sync.
- Sync Firestore user and account documents into a CRM so go-to-market teams see live product data.
Offload heavy reads
Point analytical queries at the synced copy in Dremio and keep Firebase focused on its operational workload.
Operational data in the warehouse, minus the pipeline
Rows from Firebase land in Dremio as they change, replacing hand-built CDC and batch extract jobs.
Serve warehouse results at database speed
Aggregates or model outputs computed in Dremio sync into Firebase, where whatever reads from that database gets them without querying the warehouse.
What you can sync between Dremio 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.
| Dremio objects | Firebase objects | |
|---|---|---|
| Apache Iceberg tables Lakehouse tables supporting DML and snapshot metadata usable for incremental reads. | Firestore Documents Schemaless JSON-like records, the primary unit synced to and from external systems. | |
| Spaces and folders Namespaces that organize virtual datasets and govern access. | Subcollections Nested collections under documents, typically flattened into related tables during sync. | |
| Reflections Materialized accelerations that make repeated extraction queries cheaper. | Realtime Database Nodes JSON tree paths in the older Realtime Database, synced by path. | |
| Jobs Query execution records useful for monitoring sync workloads. | Authentication Users User accounts read into CRMs and warehouses for customer records. | |
| Sources Connected storage and database systems (S3, ADLS, relational databases) Dremio queries in place. | Cloud Storage Objects Files referenced from documents; usually synced as metadata plus URLs. | |
| Physical datasets Tables and files promoted from sources; the raw data a sync ultimately reads. | Cloud Functions Triggers Server-side hooks that fire on document changes and can push updates outward. |
What ships with Dremio ⇄ Firebase
Connect Dremio and Firebase for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Dremio–Firebase connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Dremio 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 Dremio or Firebase record.
Observability
Monitoring
Track your Dremio ⇄ Firebase sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Dremio and Firebase.
How the Dremio and Firebase connectors work
Dremio
- Integration surface
- Arrow Flight SQL, JDBC/ODBC, and a REST API
- Authentication
- Personal access tokens or username/password; OAuth-based SSO on Dremio Cloud
- Change detection
- Polling via SQL; Iceberg table snapshots can anchor incremental reads; no consumer-facing change feed
- Capabilities
- read · write
- Rate limits
- Bounded by engine capacity and workload management rather than API rate limits
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 Dremio 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.
- 01
Connect your apps
Authenticate Dremio 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.
Dremio
connected
Firebase
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Dremio 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.
objects · Dremio ⇄ FirebaseCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Dremio FirebaseCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Dremio and Firebase integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Dremio and Firebase: authenticate both systems, choose the objects to sync (such as Dremio's Apache Iceberg tables and Spaces and folders), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Yes — Stacksync ships production-grade connectors for both Dremio and Firebase. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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Change detection on Dremio: Polling via SQL; Iceberg table snapshots can anchor incremental reads; no consumer-facing change feed. On Firebase: Real-time snapshot listeners on Firestore queries and Cloud Functions triggers on document changes. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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On the Dremio side: Apache Iceberg tables, Spaces and folders, Reflections, Jobs, plus custom fields where Dremio exposes them. On the Firebase side: Firestore Collections, Firestore Documents, Subcollections, Realtime Database Nodes. Stacksync auto-detects both schemas and converts types between the two systems.
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Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
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Common patterns for Dremio and Firebase: Offload heavy reads; Operational data in the warehouse, minus the pipeline; Serve warehouse results at database speed. Point analytical queries at the synced copy in Dremio and keep Firebase focused on its operational workload.
SECURITY
Security teams love 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.
SOC 2 type II
ISO 27001
HIPAA BAA
GDPR
CCPA
CSA STAR
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:
Related integrations
Every pair below is a real-time, two-way sync. Search all 386 integrations available for Dremio and Firebase.
Popular · 8 of 386
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Dremio ⇄ MarkLogic -
Dremio ⇄ Neo4j -
Dremio ⇄ OCI Database (Oracle Cloud) -
Dremio ⇄ OpenSearch -
Firebase ⇄ BigQuery -
Firebase ⇄ MotherDuck -
Firebase ⇄ Databricks -
Firebase ⇄ AWS S3
No integrations match .
