Real-time
Two-way sync
Changes in Firebolt or Postgres Heroku instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ Database
Firebolt to Postgres Heroku integration — real-time, two-way sync
Keep Firebolt and Postgres Heroku 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 Firebolt and Postgres Heroku
Connect Postgres Heroku and Firebolt 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 Postgres Heroku's rows in Firebolt, 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 Postgres Heroku where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in Postgres Heroku sync into Firebolt in real time, and result tables in Firebolt sync back into Postgres Heroku, with schema and type mapping between the two systems handled for you.
Common use cases
- Sync aggregated results from Firebolt back to operational tools that need computed metrics (reverse ETL).
- Sync CRM objects into Firebolt so customer-facing dashboards reflect recent pipeline changes.
- Keep several Heroku app databases aligned with one system of record
- Reflect billing and subscription records into the app database so product logic reads local rows
Offload heavy reads
Point analytical queries at the synced copy in Firebolt and keep Postgres Heroku focused on its operational workload.
Operational data in the warehouse, minus the pipeline
Rows from Postgres Heroku land in Firebolt as they change, replacing hand-built CDC and batch extract jobs.
Serve warehouse results at database speed
Aggregates or model outputs computed in Firebolt sync into Postgres Heroku, where whatever reads from that database gets them without querying the warehouse.
What you can sync between Firebolt and Postgres Heroku
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.
| Firebolt objects | Postgres Heroku objects | |
|---|---|---|
| Tables Managed columnar tables written with SQL; the main sync destination. | Tables Standard Postgres tables; the primary two-way sync target for app data. | |
| External tables References to files in object storage used to stage bulk loads. | Views Read-side projections exposed to outbound syncs. | |
| Views Curated query surfaces commonly used as sources for reverse ETL. | Materialized Views Precomputed result sets synced outward on refresh. | |
| Aggregating indexes Precomputed rollups maintained at write time; incremental loads update them automatically. | Schemas Namespaces that scope which tables a sync reads and writes. | |
| Engines Compute resources that must be running for a sync to read or write. | Primary and Unique Keys Match keys for idempotent upserts from connected systems. | |
| Databases Logical containers holding the tables a sync targets. | JSONB Columns Semi-structured payloads for nested SaaS objects and metadata. |
What ships with Firebolt ⇄ Postgres Heroku
Connect Firebolt and Postgres Heroku for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Firebolt–Postgres Heroku connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Firebolt or Postgres Heroku 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 Firebolt or Postgres Heroku record.
Observability
Monitoring
Track your Firebolt ⇄ Postgres Heroku sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Firebolt and Postgres Heroku.
How the Firebolt and Postgres Heroku connectors work
Firebolt
- Integration surface
- SQL over a REST API, with JDBC, Python, and Node.js SDKs
- Authentication
- Service account credentials (client ID and secret) exchanged for OAuth 2.0 tokens
- Change detection
- Polling; Firebolt is an analytics destination and does not expose a change feed
- Capabilities
- read · write
- Rate limits
- No fixed request quota; throughput depends on the engine size attached to the workload
Postgres Heroku
- Integration surface
- SQL wire protocol (standard PostgreSQL)
- Authentication
- Database credentials from the Heroku DATABASE_URL config var; SSL required
- Change detection
- Trigger-based capture or polling in most configurations; log-based logical replication availability depends on plan and Heroku's managed server settings
- Capabilities
- read · write
- Rate limits
- No API rate limits; connection counts and performance are bounded by the Heroku Postgres plan
How it works
How to connect Firebolt to Postgres Heroku — 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 Firebolt and Postgres Heroku with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Firebolt
connected
Postgres Heroku
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Firebolt and Postgres Heroku 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 · Firebolt ⇄ Postgres HerokuCustomers 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.
Firebolt Postgres HerokuCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Firebolt and Postgres Heroku integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Firebolt and Postgres Heroku: authenticate both systems, choose the objects to sync (such as Firebolt's Tables and External tables), map fields visually, and changes propagate both ways in milliseconds — no code required.
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On the Firebolt side: Engines, Databases, Tables, External tables, plus custom fields where Firebolt exposes them. On the Postgres Heroku side: Follower Databases, Tables, Views, Materialized Views. 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.
-
Common patterns for Firebolt and Postgres Heroku: 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 Firebolt and keep Postgres Heroku focused on its operational workload.
-
Firebolt: SQL over a REST API, with JDBC, Python, and Node.js SDKs. Authentication: Service account credentials (client ID and secret) exchanged for OAuth 2.0 tokens. Postgres Heroku: SQL wire protocol (standard PostgreSQL). Authentication: Database credentials from the Heroku DATABASE_URL config var; SSL required. Stacksync manages authentication, retries, and rate limits on both sides.
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Firebolt: Compute is organized into engines that start and stop independently of storage, so sync schedules interact with engine availability and cost. Postgres Heroku: Heroku Postgres is standard PostgreSQL, so any Postgres client, driver, or SQL tool connects unchanged. Stacksync's field mapping accounts for these differences between Firebolt and Postgres Heroku without custom code.
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 Firebolt and Postgres Heroku.
Popular · 8 of 386
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Firebolt ⇄ Oracle DB -
Firebolt ⇄ RavenDB -
Firebolt ⇄ Redis Enterprise -
Firebolt ⇄ SAP ASE (Sybase) -
Postgres Heroku ⇄ AWS S3 -
Postgres Heroku ⇄ Actian Vector -
Postgres Heroku ⇄ Amazon Redshift -
Postgres Heroku ⇄ Apache Doris
No integrations match .
