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Business productivity ⇄ Database

BetterContact to PostgreSQL integration — real-time data sync

Keep BetterContact and PostgreSQL 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

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Why teams connect BetterContact and PostgreSQL

Mirror BetterContact's data into PostgreSQL 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 PostgreSQL, so PostgreSQL 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 PostgreSQL.

Stacksync mirrors Enriched Contact, Company, Lead Finder Search, Enrichment Request from BetterContact into Primary and Unique Keys, JSONB Columns, Sequences, Custom Types and Enums in PostgreSQL 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 Feed outbound sequencing tools with verified contact data before campaigns launch.
  • 02 Validate catch-all email addresses before sending to protect sender domain reputation.
  • 03 Let an application write to its own database and have those rows appear as records in business systems in near real time
  • 04 Consolidate data from several microservice databases into one operational Postgres store

Common sync patterns

React to changes as they happen

Updates in BetterContact arrive as row changes in PostgreSQL, so triggers, jobs, and services can respond in near real time.

One integration pattern for the whole stack

Every synced tool looks the same from the database, so each new integration is configuration, not a new codebase.

Read BetterContact with a query

Records from BetterContact are ordinary rows in PostgreSQL; join them, index them, and use them in application logic without touching the vendor API.

What you can sync between BetterContact and PostgreSQL

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 PostgreSQL objects How this pairing syncs
Enriched Contact Verified work emails and mobile numbers with job title, LinkedIn profile, location, and skills. Custom Types and Enums Constrain synced values to a fixed set, mirroring picklist fields. Enriched Contact is specific to BetterContact and Custom Types and Enums to PostgreSQL — 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 The primary sync target; rows map one-to-one to records in connected SaaS systems. Company is specific to BetterContact and Tables to PostgreSQL — 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 used to expose joined or filtered data to a sync. Lead Finder Search is specific to BetterContact and Views to PostgreSQL — each maps to any object or custom field on the other side.
Enrichment Request Batch or single submissions of up to 100 contacts per request for waterfall enrichment. Materialized Views Precomputed result sets synced outward on a refresh schedule. Enrichment Request is specific to BetterContact and Materialized Views to PostgreSQL — each maps to any object or custom field on the other side.

How changes propagate between BetterContact and PostgreSQL

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 PostgreSQL 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 PostgreSQL as a row-level write, with types converted between the two schemas.

PostgreSQL BetterContact Sub-second propagation

DetectionChanges in PostgreSQL are captured at the source via change data capture — no polling loop against its API. Logical replication (wal_level = logical) for change data capture via the "Postgres" connector.

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 PostgreSQL records.

Rate-limit considerations

  • BetterContact: Batches capped at 100 contacts per enrichment request.
  • PostgreSQL: No API rate limits; throughput is bounded by connection limits, instance resources, and replication slot throughput.
What ships with BetterContact ⇄ PostgreSQL

Connect BetterContact and PostgreSQL for flexible, real-time data sync.

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

Real-time

Real-time sync

Changes in BetterContact or PostgreSQL instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever BetterContact or PostgreSQL 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 PostgreSQL record.

Observability

Monitoring

Track your BetterContact ⇄ PostgreSQL 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 PostgreSQL.

How the BetterContact and PostgreSQL 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.

PostgreSQL

Integration surface
SQL wire protocol (PostgreSQL frontend/backend protocol)
Authentication
Database credentials (connection string or parameters), with optional SSL root certificate upload and optional SSH tunnel (SSH user + host); a least-privilege DB user
Change detection
Logical replication (wal_level = logical) for change data capture via the "Postgres" connector; database triggers (TRIGGER grant + stacksync_logging schema) via the trigger-based "Postgres Heroku" connector where
Capabilities
read · write · CDC
Rate limits
No API rate limits; throughput is bounded by connection limits, instance resources, and replication slot throughput
PostgreSQL setup guide
How it works

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

    Choose tables

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

BetterContact and PostgreSQL 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
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:

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 390 integrations available for BetterContact and PostgreSQL.

Popular · 8 of 390
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