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Database ⇄ Business productivity

AWS Aurora PostgreSQL to BetterContact integration — real-time data sync

Keep AWS Aurora PostgreSQL and BetterContact 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 AWS Aurora PostgreSQL and BetterContact

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

Stacksync mirrors Enrichment Request, Enriched Contact, Company, Lead Finder Search from BetterContact into Rows, Columns, Primary keys and constraints, Views and materialized views in AWS Aurora 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 Expose ERP records such as customers, orders, and invoices as Postgres tables the engineering team can query and update with plain SQL.
  • 04 Capture row-level changes with logical replication and propagate them to SaaS tools without batch jobs.

Common sync patterns

Automate BetterContact from your codebase

Write to the synced tables in AWS Aurora PostgreSQL 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 AWS Aurora 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.

What you can sync between AWS Aurora PostgreSQL and BetterContact

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.

AWS Aurora PostgreSQL objects BetterContact objects How this pairing syncs
Primary keys and constraints Identify rows for upserts and enforce integrity on sync writes. Company Company data returned with each contact: name, domain, HQ location, industry, employee count. Primary keys and constraints is specific to AWS Aurora PostgreSQL and Company to BetterContact — each maps to any object or custom field on the other side.
Views and materialized views Usable as read-only sources for filtered or precomputed sync datasets. Lead Finder Search Prospect discovery by people and company filters, returning enriched lead profiles. Views and materialized views is specific to AWS Aurora PostgreSQL and Lead Finder Search to BetterContact — each maps to any object or custom field on the other side.
Foreign keys Relationship metadata that syncs can translate into object references elsewhere. Enrichment Request Batch or single submissions of up to 100 contacts per request for waterfall enrichment. Foreign keys is specific to AWS Aurora PostgreSQL and Enrichment Request to BetterContact — each maps to any object or custom field on the other side.
Replication slots and publications The logical replication objects that power log-based CDC. Enriched Contact Verified work emails and mobile numbers with job title, LinkedIn profile, location, and skills. Replication slots and publications is specific to AWS Aurora PostgreSQL and Enriched Contact to BetterContact — each maps to any object or custom field on the other side.

How changes propagate between AWS Aurora PostgreSQL and BetterContact

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.

AWS Aurora PostgreSQL BetterContact Sub-second propagation

DetectionChanges in AWS Aurora PostgreSQL are captured at the source via change data capture — no polling loop against its API. Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback.

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 AWS Aurora PostgreSQL records.

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

Rate-limit considerations

  • BetterContact: Batches capped at 100 contacts per enrichment request.
What ships with AWS Aurora PostgreSQL ⇄ BetterContact

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

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

Real-time

Real-time sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever AWS Aurora PostgreSQL or BetterContact 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 AWS Aurora PostgreSQL or BetterContact record.

Observability

Monitoring

Track your AWS Aurora PostgreSQL ⇄ BetterContact sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between AWS Aurora PostgreSQL and BetterContact.

How the AWS Aurora PostgreSQL and BetterContact connectors work

AWS Aurora PostgreSQL

Integration surface
SQL wire protocol (PostgreSQL-compatible), standard Postgres drivers and JDBC
Authentication
Database credentials, optionally AWS IAM database authentication, over TLS
Change detection
Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback
Capabilities
read · write · CDC

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.
How it works

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

    Choose tables

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

AWS Aurora PostgreSQL and BetterContact 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
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DPF US-EU-UK-CH
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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 AWS Aurora PostgreSQL and BetterContact.

Popular · 8 of 390
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