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CRM ⇄ Database

DealCloud to PostgreSQL integration — real-time, two-way sync

Keep DealCloud 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 DealCloud and PostgreSQL

Treat DealCloud like part of your database: its records live in PostgreSQL as real tables, and writes in either place sync to the other in seconds.

Product and engineering teams constantly need CRM data, and the CRM API is a poor way to get it: rate limits, pagination, custom objects, and integration code that breaks when an admin renames a field. What they actually want is the data in PostgreSQL, where it can be queried and joined like everything else.

Stacksync mirrors Fund, Investment, Relationship, Activity from DealCloud into Tables, Views, Materialized Views, Schemas in PostgreSQL with real-time, bi-directional sync. Read CRM records with plain queries; write updates from your application and they appear in DealCloud with validation intact. Go-to-market teams keep working in the CRM, engineers keep working in the database, and neither has to think about the other.

Common use cases

  • 01 Keep DealCloud contacts and relationships in sync with an enrichment or email platform to maintain accurate firm-wide relationship intelligence.
  • 02 Mirror DealCloud activities and tasks into an operational database to power internal dashboards without hitting the API on every read.
  • 03 Expose SaaS objects (CRM contacts, ERP invoices, support tickets) as Postgres tables that internal tools can query and join
  • 04 Let an application write to its own database and have those rows appear as records in business systems in near real time

Common sync patterns

Product events onto CRM records

Signup, usage, or lifecycle changes written to PostgreSQL sync onto the matching records in DealCloud, giving go-to-market teams live product context.

Internal tools without API code

Back-office apps read and write the synced tables; Stacksync handles the DealCloud API, limits, and retries.

Trigger workflows from CRM changes

Field and stage updates in DealCloud arrive as row changes in PostgreSQL, ready to drive jobs and notifications.

What you can sync between DealCloud 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.

DealCloud objects PostgreSQL objects How this pairing syncs
Investment Synced with incremental and full sync. Materialized Views Precomputed result sets synced outward on a refresh schedule. Investment is specific to DealCloud and Materialized Views to PostgreSQL — each maps to any object or custom field on the other side.
Relationship Synced with incremental and full sync. Schemas Namespaces that scope which tables a sync reads and writes. Relationship is specific to DealCloud and Schemas to PostgreSQL — each maps to any object or custom field on the other side.
Activity Synced with incremental and full sync. Columns Field-level mapping targets; types are mapped to the connected system's field types. Activity is specific to DealCloud and Columns to PostgreSQL — each maps to any object or custom field on the other side.
Task Synced with incremental and full sync. Primary and Unique Keys Used as match keys for idempotent upserts and conflict resolution. Task is specific to DealCloud and Primary and Unique Keys to PostgreSQL — each maps to any object or custom field on the other side.
User Synced with incremental and full sync. JSONB Columns Hold semi-structured payloads such as nested SaaS objects or metadata. User is specific to DealCloud and JSONB Columns to PostgreSQL — each maps to any object or custom field on the other side.
Deal Synced with incremental and full sync. Sequences Generate surrogate keys for rows created by inbound syncs. Deal is specific to DealCloud and Sequences to PostgreSQL — each maps to any object or custom field on the other side.

How changes propagate between DealCloud 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.

DealCloud PostgreSQL Interval-based propagation

DetectionStacksync polls DealCloud for changes on an incremental schedule, reading only records changed since the previous pass. Incremental via each entry's last-modified timestamp.

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

PostgreSQL DealCloud 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.

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

Rate-limit considerations

  • DealCloud: API request limits apply per firm tenant; Stacksync manages throttling and retries automatically.
  • PostgreSQL: No API rate limits; throughput is bounded by connection limits, instance resources, and replication slot throughput.
What ships with DealCloud ⇄ PostgreSQL

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever DealCloud 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 DealCloud or PostgreSQL record.

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between DealCloud and PostgreSQL.

How the DealCloud and PostgreSQL connectors work

DealCloud

Integration surface
REST API (DealCloud Data API v2)
Authentication
OAuth 2.0 client-credentials; a DealCloud administrator generates a client ID and secret in the DealCloud admin API settings and grants Stacksync the required scopes
Change detection
Incremental via each entry's last-modified timestamp; DealCloud has no universal native change-data-capture, so Stacksync polls modified rows on an interval
Capabilities
read · write
Rate limits
API request limits apply per firm tenant; Stacksync manages throttling and retries automatically.

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 DealCloud 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 DealCloud 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
    DealCloud connected
    PostgreSQL connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

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

DealCloud 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 392 integrations available for DealCloud and PostgreSQL.

Popular · 8 of 392
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