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Database ⇄ Marketing

AWS Aurora PostgreSQL to Demandbase integration — real-time, two-way sync

Keep AWS Aurora PostgreSQL and Demandbase in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect AWS Aurora PostgreSQL and Demandbase

Give your team Demandbase's contacts, campaigns, and engagement in AWS Aurora PostgreSQL: query them with SQL, push audiences built from your own data back to Demandbase, and skip the marketing API.

Demandbase holds the people, audiences, and campaign activity that marketing runs on, but that data sits behind interfaces built for marketers, not for your internal systems. Engineers and analysts who need contacts, list membership, or engagement, for reporting, attribution, or product logic, end up writing integration code against a rate-limited API and maintaining it forever. Meanwhile the customer and usage data marketers want for targeting already lives in AWS Aurora PostgreSQL, hard to get into campaigns without manual exports.

Stacksync mirrors Change Subscriptions, Accounts, Opportunities, People (Persons) from Demandbase into Tables, Rows, Columns, Primary keys and constraints in AWS Aurora PostgreSQL field by field, in real time, and in both directions. Marketing records become rows your code can query and join with product and customer data; audiences and attributes computed in AWS Aurora PostgreSQL, from usage, orders, or account status, sync back into Demandbase to drive campaigns and ads, with Demandbase kept authoritative for engagement. You decide which side owns which fields, and Stacksync resolves conflicts by rules you set.

Common use cases

  • 01 Capture row-level changes with logical replication and propagate them to SaaS tools without batch jobs.
  • 02 Sync JSONB-heavy application data into structured objects in downstream business systems.
  • 03 Sync Opportunities and Activities two-way so CRM deal and engagement data flows into Demandbase reporting and Demandbase-calculated insights flow back to the warehouse.
  • 04 Subscribe to Demandbase company and person change webhooks - firmographic updates, M&A, and leadership or employment changes - and land them in an operational store for real-time account alerts.

Common sync patterns

Keep contact attributes consistent

Lifecycle stage, subscription status, or plan maintained on either side stays current on the other, ending exports and dual data entry.

Query Demandbase like a database

Contacts, leads, audiences, and campaign metrics from Demandbase live in AWS Aurora PostgreSQL as ordinary tables or collections, joinable with the rest of your data and reachable without touching the vendor API.

Build audiences from your own data

Segments computed in AWS Aurora PostgreSQL from product usage, orders, or account status sync into Demandbase as lists or audiences, so campaigns and ads target the people your data says they should.

What you can sync between AWS Aurora PostgreSQL and Demandbase

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 Demandbase objects How this pairing syncs
Tables The core sync unit; rows are matched across systems by primary key. Accounts Company/account records with firmographics, intent, and Demandbase qualification and engagement scores; exported via the Data Export API and imported or updated via the Data Import API. Tables is specific to AWS Aurora PostgreSQL and Accounts to Demandbase — each maps to any object or custom field on the other side.
Rows Inserted, updated, and deleted in both directions during bi-directional syncs. Opportunities Opportunity records synced from the CRM into Demandbase; exported with calculated insights and imported or updated through the Data Import API. Read and write. Rows is specific to AWS Aurora PostgreSQL and Opportunities to Demandbase — each maps to any object or custom field on the other side.
Columns Rich Postgres types including JSONB and arrays are mapped to the paired system's fields. People (Persons) Contact/person records with verified business email, title, seniority, and quality grades; fetched and matched via the B2B Contact endpoints and exported or imported. Columns is specific to AWS Aurora PostgreSQL and People (Persons) to Demandbase — each maps to any object or custom field on the other side.
Primary keys and constraints Identify rows for upserts and enforce integrity on sync writes. Activities Engagement and custom activity records (web, campaign, intent); exported via Data Export and pushed in through the Data Import API using custom activity types. Primary keys and constraints is specific to AWS Aurora PostgreSQL and Activities to Demandbase — 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. Campaigns Marketing campaign records and creative assets exported through the Data Export API; read-only reporting feed. Views and materialized views is specific to AWS Aurora PostgreSQL and Campaigns to Demandbase — each maps to any object or custom field on the other side.
Foreign keys Relationship metadata that syncs can translate into object references elsewhere. Account & Person Lists (Audiences) Named account and person segments exported via Data Export; custom audiences pushed into Demandbase through the Data Import API. Read and write. Foreign keys is specific to AWS Aurora PostgreSQL and Account & Person Lists (Audiences) to Demandbase — each maps to any object or custom field on the other side.

How changes propagate between AWS Aurora PostgreSQL and Demandbase

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 Demandbase 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.

DeliveryEach detected change is written to Demandbase through its API, with automatic retries and rate-limit backoff.

Demandbase AWS Aurora PostgreSQL Sub-second propagation

DetectionDemandbase notifies Stacksync of record changes through webhook events. Subscription API webhooks - company firmographic, company news, family-tree (ownership), and person employment-change alerts to a configurable URL.

DeliveryEach detected change is applied to AWS Aurora PostgreSQL as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Demandbase: Credit-based per API call; bulk jobs accept up to 10,000 records per submission, CSV uploads up to 5GB, and result URLs stay valid 24 hours; subscription alerts page up to 5,000 entities and list endpoints up to 100 per page.
What ships with AWS Aurora PostgreSQL ⇄ Demandbase

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

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

Real-time

Two-way sync

Changes in AWS Aurora PostgreSQL or Demandbase 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 Demandbase 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 Demandbase record.

Observability

Monitoring

Track your AWS Aurora PostgreSQL ⇄ Demandbase 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 Demandbase.

How the AWS Aurora PostgreSQL and Demandbase 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

Demandbase

Integration surface
REST APIs (Demandbase One) - a B2B API (company/contact search, details, and match with async bulk enrichment jobs), a read-only Data Export API and a write-capable Data Import API (both async bulk jobs), and a Subscription API for webhook change alerts.
Authentication
JWT bearer tokens minted from Demandbase One API Key Sets at the platform level; each credential set expires after 8 hours and is rotated. Legacy single-user API tokens are deprecated.
Change detection
Subscription API webhooks - company firmographic, company news, family-tree (ownership), and person employment-change alerts to a configurable URL secured with a signing secret; bulk reads run as async export jobs (submit, poll, download). No log-based CDC.
Capabilities
read · write · webhooks
Rate limits
Credit-based per API call; bulk jobs accept up to 10,000 records per submission, CSV uploads up to 5GB, and result URLs stay valid 24 hours; subscription alerts page up to 5,000 entities and list endpoints up to 100 per page.
How it works

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

    Choose tables

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

AWS Aurora PostgreSQL and Demandbase 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
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 412 integrations available for AWS Aurora PostgreSQL and Demandbase.

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