Real-time
Two-way sync
Changes in Elasticsearch or Firebase instantly reflect in both systems. No stale data, no manual imports.
Database
Elasticsearch to Firebase integration — real-time, two-way sync
Keep Elasticsearch 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
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Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Elasticsearch and Firebase
Keep Elasticsearch and Firebase synchronized in real time, across engines, regions, or services, in one or both directions.
Two databases that must agree is one of the oldest problems in engineering: different engines for different workloads, separate services with overlapping reference data, a migration in flight, or regional instances that share a subset of records. Hand-rolled replication across systems means change capture, conflict handling, and type mapping, all built and maintained by your team.
Stacksync syncs tables or collections between Elasticsearch and Firebase continuously and bi-directionally, translating types between the two engines and resolving conflicts by rules you configure. Rows written on either side appear on the other within seconds.
Common use cases
- Feed enriched customer records into an index used for vector or hybrid search in AI applications.
- Sync CRM accounts and contacts into an Elasticsearch index to power internal search across customer records.
- Mirror Firestore collections into Postgres or a warehouse to run SQL analytics on app data.
- Write CRM-side changes (plan, status, owner) back into Firestore documents the app reads.
Shared reference data between services
Services that own separate databases stay consistent on the records they share, without a custom replication layer.
Regional or environment copies
Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.
Cross-engine sync
Keep the same dataset live in both Elasticsearch and Firebase, so each workload runs on the engine that suits it.
What you can sync between Elasticsearch 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.
| Elasticsearch objects | Firebase objects | |
|---|---|---|
| Aliases Stable read/write names that let a sync cut over between index versions without downtime. | Firestore Documents Schemaless JSON-like records, the primary unit synced to and from external systems. | |
| Data streams Append-only targets for time-series or event data pushed from source systems. | Subcollections Nested collections under documents, typically flattened into related tables during sync. | |
| Ingest pipelines Server-side transforms applied to documents as a sync writes them. | Realtime Database Nodes JSON tree paths in the older Realtime Database, synced by path. | |
| Index templates Reusable settings and mappings applied automatically to new indices a sync creates. | Authentication Users User accounts read into CRMs and warehouses for customer records. | |
| Indices Target containers for synced records; each holds a table-like collection of JSON documents. | Cloud Storage Objects Files referenced from documents; usually synced as metadata plus URLs. | |
| Documents The unit of sync; JSON records created, updated, and deleted by _id. | Cloud Functions Triggers Server-side hooks that fire on document changes and can push updates outward. |
What ships with Elasticsearch ⇄ Firebase
Connect Elasticsearch and Firebase for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Elasticsearch–Firebase connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Elasticsearch 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 Elasticsearch or Firebase record.
Observability
Monitoring
Track your Elasticsearch ⇄ Firebase sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Elasticsearch and Firebase.
How the Elasticsearch and Firebase connectors work
Elasticsearch
- Integration surface
- REST API (JSON over HTTP)
- Authentication
- API keys or basic authentication; Elastic Cloud also issues service account tokens
- Change detection
- Polling on timestamp or sequence fields; Elasticsearch does not expose a native change feed or webhooks
- Capabilities
- read · write
- Rate limits
- No fixed request quota; throughput is bounded by cluster sizing, thread pools, and bulk queue capacity
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 Elasticsearch 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 Elasticsearch 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.
Elasticsearch
connected
Firebase
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Elasticsearch 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 · Elasticsearch ⇄ 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.
Elasticsearch FirebaseCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Elasticsearch and Firebase integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Elasticsearch and Firebase: authenticate both systems, choose the objects to sync (such as Elasticsearch's Aliases and Data streams), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means Elasticsearch and Firebase records are not retained after a sync operation.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed Elasticsearch and Firebase connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Elasticsearch–Firebase integration in-house.
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Yes — Stacksync ships production-grade connectors for both Elasticsearch 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 Elasticsearch: Polling on timestamp or sequence fields; Elasticsearch does not expose a native change feed or webhooks. 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 Elasticsearch side: Ingest pipelines, Index templates, Indices, Documents, plus custom fields where Elasticsearch exposes them. On the Firebase side: Cloud Functions Triggers, Firestore Collections, Firestore Documents, Subcollections. Stacksync auto-detects both schemas and converts types between the two systems.
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 Elasticsearch and Firebase.
Popular · 8 of 386
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Elasticsearch ⇄ Citus -
Elasticsearch ⇄ Couchbase -
Elasticsearch ⇄ DuckDB -
Elasticsearch ⇄ Google Cloud Spanner -
Firebase ⇄ SAP ASE (Sybase) -
Firebase ⇄ Scaleway Postgres -
Firebase ⇄ TiDB -
Firebase ⇄ TimescaleDB
No integrations match .
