Real-time
Real-time sync
Changes in BetterContact or Postgres Heroku instantly reflect in both systems. No stale data, no manual imports.
Business productivity ⇄ Database
BetterContact to Postgres Heroku integration — real-time data sync
Keep BetterContact 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
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Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
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Migrated from Fivetran
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Migrated from Celigo
Why teams connect BetterContact and Postgres Heroku
Mirror BetterContact's data into Postgres Heroku so your own code can read and write it like any other table, with changes flowing both ways in seconds.
BetterContact is a read-only source: Stacksync reads its data in real time and delivers it into Postgres Heroku, so Postgres Heroku always reflects the current state of BetterContact — without exports, scripts, or schedulers.
Engineers integrate with tools like BetterContact through APIs, which means auth, pagination, rate limits, webhooks, and retry logic, all maintained forever and all different for every tool. Meanwhile the data would be trivial to use if it simply lived in Postgres Heroku.
Stacksync mirrors Lead Finder Search, Enrichment Request, Enriched Contact, Company from BetterContact into Tables, Views, Materialized Views, Schemas in Postgres Heroku and keeps both sides in sync in real time. Your services query the database directly, and inserts or updates your code makes flow back into BetterContact, so the tool and the database never disagree.
Common use cases
- 01 Backfill a warehouse of contacts with waterfall enrichment across 20+ data providers.
- 02 Feed outbound sequencing tools with verified contact data before campaigns launch.
- 03 Expose CRM objects as Postgres tables the Heroku application can query and join directly
- 04 Sync Heroku Postgres into a warehouse for reporting without running ETL dynos
Common sync patterns
Read BetterContact with a query
Records from BetterContact are ordinary rows in Postgres Heroku; join them, index them, and use them in application logic without touching the vendor API.
Automate BetterContact from your codebase
Write to the synced tables in Postgres Heroku and Stacksync propagates the change into BetterContact, replacing custom integration code.
React to changes as they happen
Updates in BetterContact arrive as row changes in Postgres Heroku, so triggers, jobs, and services can respond in near real time.
What you can sync between BetterContact 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.
| BetterContact objects | Postgres Heroku objects | How this pairing syncs | |
|---|---|---|---|
| Enrichment Request Batch or single submissions of up to 100 contacts per request for waterfall enrichment. | Sequences Generate surrogate keys for rows created by inbound syncs. | Enrichment Request is specific to BetterContact and Sequences to Postgres Heroku — each maps to any object or custom field on the other side. | |
| Enriched Contact Verified work emails and mobile numbers with job title, LinkedIn profile, location, and skills. | Follower Databases Heroku-managed read replicas usable as low-impact sync sources. | Enriched Contact is specific to BetterContact and Follower Databases to Postgres Heroku — each maps to any object or custom field on the other side. | |
| Company Company data returned with each contact: name, domain, HQ location, industry, employee count. | Tables Standard Postgres tables; the primary two-way sync target for app data. | Company is specific to BetterContact and Tables to Postgres Heroku — each maps to any object or custom field on the other side. | |
| Lead Finder Search Prospect discovery by people and company filters, returning enriched lead profiles. | Views Read-side projections exposed to outbound syncs. | Lead Finder Search is specific to BetterContact and Views to Postgres Heroku — each maps to any object or custom field on the other side. |
How changes propagate between BetterContact and Postgres Heroku
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.
BetterContact Postgres Heroku Sub-second propagation
DetectionBetterContact notifies Stacksync of record changes through webhook events. Job-based delivery — enrichment results arrive by webhook push or polling of the results endpoint.
DeliveryEach detected change is applied to Postgres Heroku as a row-level write, with types converted between the two schemas.
Postgres Heroku BetterContact Interval-based propagation
DetectionStacksync polls Postgres Heroku for changes on an incremental schedule, reading only records changed since the previous pass. Trigger-based capture or polling in most configurations.
DeliveryBetterContact does not accept inbound record writes, so this direction carries requests rather than records: BetterContact's output flows back as field updates on the originating Postgres Heroku records.
Rate-limit considerations
- BetterContact: Batches capped at 100 contacts per enrichment request.
- Postgres Heroku: No API rate limits; connection counts and performance are bounded by the Heroku Postgres plan.
What ships with BetterContact ⇄ Postgres Heroku
Connect BetterContact and Postgres Heroku for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every BetterContact–Postgres Heroku connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever BetterContact 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 BetterContact or Postgres Heroku record.
Observability
Monitoring
Track your BetterContact ⇄ 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 BetterContact and Postgres Heroku.
How the BetterContact and Postgres Heroku connectors work
BetterContact
- Integration surface
- Asynchronous REST API: submit contacts, then receive results via webhook or fetch them from a results endpoint
- Authentication
- API key
- Change detection
- Job-based delivery — enrichment results arrive by webhook push or polling of the results endpoint; there is no persistent record store to watch
- Capabilities
- read · webhooks
- Rate limits
- Batches capped at 100 contacts per enrichment request.
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 BetterContact 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 BetterContact 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.
BetterContact
connected
Postgres Heroku
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the BetterContact 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 · BetterContact ⇄ 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.
BetterContact Postgres HerokuCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
BetterContact and Postgres Heroku integration FAQ
-
Yes. Stacksync provides a managed, real-time integration between BetterContact and Postgres Heroku — BetterContact is a read-only source, so data flows from it into the other system: authenticate both systems, choose the objects to sync, map fields visually, and changes propagate in milliseconds — no code required.
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Yes — Stacksync ships production-grade connectors for both BetterContact and Postgres Heroku. 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 BetterContact: Job-based delivery — enrichment results arrive by webhook push or polling of the results endpoint; there is no persistent record store to watch. On Postgres Heroku: Trigger-based capture or polling in most configurations; log-based logical replication availability depends on plan and Heroku's managed server settings. 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 BetterContact side: Lead Finder Search, Enrichment Request, Enriched Contact, Company, plus custom fields where BetterContact exposes them. On the Postgres Heroku side: Tables, Views, Materialized Views, Schemas. Stacksync auto-detects both schemas and converts types between the two systems.
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BetterContact is a read-only source, so this integration runs one-way: Stacksync reads from BetterContact in real time and delivers into Postgres Heroku. Field mapping and monitoring work the same as for two-way pairs.
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Common patterns for BetterContact and Postgres Heroku: Read BetterContact with a query; Automate BetterContact from your codebase; React to changes as they happen. Records from BetterContact are ordinary rows in Postgres Heroku; join them, index them, and use them in application logic without touching the vendor API.
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.
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:
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