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CRM ⇄ Database

DealCloud to Google Cloud SQL integration — real-time, two-way sync

Keep DealCloud and Google Cloud SQL 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 Google Cloud SQL

Treat DealCloud like part of your database: its records live in Google Cloud SQL 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 Google Cloud SQL, where it can be queried and joined like everything else.

Stacksync mirrors Task, User, Deal, Company from DealCloud into Views, Transaction logs, Instances, Databases in Google Cloud SQL 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 Push portfolio and fund performance data from a warehouse into DealCloud so dealmakers see up-to-date metrics on each investment.
  • 02 Keep DealCloud contacts and relationships in sync with an enrichment or email platform to maintain accurate firm-wide relationship intelligence.
  • 03 Migrate from a self-managed database by syncing Cloud SQL and the legacy system during cutover.
  • 04 Keep an internal admin application backed by Cloud SQL consistent with an ERP or billing system.

Common sync patterns

Trigger workflows from CRM changes

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

Query the CRM like a database

Accounts, contacts, and custom objects from DealCloud become tables in Google Cloud SQL you can join with application data directly.

Product events onto CRM records

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

What you can sync between DealCloud and Google Cloud SQL

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 Google Cloud SQL objects How this pairing syncs
Company Synced with incremental and full sync. Views Read-only sources for shaping data before syncing it out. Company is specific to DealCloud and Views to Google Cloud SQL — each maps to any object or custom field on the other side.
Contact Synced with incremental and full sync. Transaction logs MySQL binlog or PostgreSQL WAL, the source for log-based change capture. Contact is specific to DealCloud and Transaction logs to Google Cloud SQL — each maps to any object or custom field on the other side.
Fund Synced with incremental and full sync. Instances The managed MySQL, PostgreSQL, or SQL Server server a sync connects to. Fund is specific to DealCloud and Instances to Google Cloud SQL — each maps to any object or custom field on the other side.
Investment Synced with incremental and full sync. Databases Scope the tables included in a sync configuration. Investment is specific to DealCloud and Databases to Google Cloud SQL — each maps to any object or custom field on the other side.
Relationship Synced with incremental and full sync. Schemas Namespace tables in PostgreSQL and SQL Server instances. Relationship is specific to DealCloud and Schemas to Google Cloud SQL — each maps to any object or custom field on the other side.
Activity Synced with incremental and full sync. Tables Mapped directly to sync targets; schema changes can be propagated. Activity is specific to DealCloud and Tables to Google Cloud SQL — each maps to any object or custom field on the other side.

How changes propagate between DealCloud and Google Cloud SQL

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 Google Cloud SQL 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 Google Cloud SQL as a row-level write, with types converted between the two schemas.

Google Cloud SQL DealCloud Sub-second propagation

DetectionChanges in Google Cloud SQL are captured at the source via change data capture — no polling loop against its API. Engine-dependent log-based CDC: MySQL binlog, PostgreSQL logical replication, SQL Server change tracking.

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.
  • Google Cloud SQL: Constrained by instance size and connection limits rather than API quotas.
What ships with DealCloud ⇄ Google Cloud SQL

Connect DealCloud and Google Cloud SQL for flexible, real-time data sync.

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever DealCloud or Google Cloud SQL 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 Google Cloud SQL record.

Observability

Monitoring

Track your DealCloud ⇄ Google Cloud SQL 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 Google Cloud SQL.

How the DealCloud and Google Cloud SQL 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.

Google Cloud SQL

Integration surface
Native SQL wire protocols (MySQL, PostgreSQL, SQL Server) plus a REST admin API for instance management
Authentication
Database credentials; IAM database authentication is available for MySQL and PostgreSQL
Change detection
Engine-dependent log-based CDC: MySQL binlog, PostgreSQL logical replication, SQL Server change tracking; polling as a fallback
Capabilities
read · write · CDC
Rate limits
Constrained by instance size and connection limits rather than API quotas.
How it works

How to connect DealCloud to Google Cloud SQL — 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 Google Cloud SQL 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
    Google Cloud SQL connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the DealCloud and Google Cloud SQL 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 ⇄ Google Cloud SQL
    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 Google Cloud SQL
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

DealCloud and Google Cloud SQL 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 Google Cloud SQL.

Popular · 8 of 392
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