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Database ⇄ CRM

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

Keep Citus and DealCloud 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 Citus and DealCloud

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

Stacksync mirrors Fund, Investment, Relationship, Activity from DealCloud into Views, Sequences, Distributed tables, Reference tables in Citus 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 Write CRM or billing records into reference tables so distributed queries can join operational context locally on every node.
  • 04 Use a Citus cluster as the scalable operational store behind a customer-facing app while syncing summaries back to internal tools.

Common sync patterns

Query the CRM like a database

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

Product events onto CRM records

Signup, usage, or lifecycle changes written to Citus 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.

What you can sync between Citus and DealCloud

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.

Citus objects DealCloud objects How this pairing syncs
Views Curated projections over distributed data, often used as read-only sync sources. Relationship Synced with incremental and full sync. Views is specific to Citus and Relationship to DealCloud — each maps to any object or custom field on the other side.
Sequences Key generators that matter when external writes must not collide with application inserts. Activity Synced with incremental and full sync. Sequences is specific to Citus and Activity to DealCloud — each maps to any object or custom field on the other side.
Distributed tables Tables sharded across worker nodes by a distribution column; the main sync target for large datasets. Task Synced with incremental and full sync. Distributed tables is specific to Citus and Task to DealCloud — each maps to any object or custom field on the other side.
Reference tables Small lookup tables replicated to every node, synced like ordinary Postgres tables. User Synced with incremental and full sync. Reference tables is specific to Citus and User to DealCloud — each maps to any object or custom field on the other side.
Local tables Coordinator-only tables that behave exactly like standard PostgreSQL tables. Deal Synced with incremental and full sync. Local tables is specific to Citus and Deal to DealCloud — each maps to any object or custom field on the other side.
Schemas Standard Postgres namespaces used to scope what a sync user can read and write. Company Synced with incremental and full sync. Schemas is specific to Citus and Company to DealCloud — each maps to any object or custom field on the other side.

How changes propagate between Citus and DealCloud

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.

Citus DealCloud Sub-second propagation

DetectionChanges in Citus are captured at the source via change data capture — no polling loop against its API. PostgreSQL logical decoding / CDC, with caveats: changes to distributed tables occur on worker shards, so CDC setup differs from single-node Postgres.

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

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

Rate-limit considerations

  • DealCloud: API request limits apply per firm tenant; Stacksync manages throttling and retries automatically.
What ships with Citus ⇄ DealCloud

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Citus or DealCloud 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 Citus or DealCloud record.

Observability

Monitoring

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

Trading partners

EDI

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

How the Citus and DealCloud connectors work

Citus

Integration surface
PostgreSQL wire protocol; any standard Postgres driver connects to the coordinator node
Authentication
Database credentials (standard PostgreSQL authentication; managed deployments add cloud IAM options)
Change detection
PostgreSQL logical decoding / CDC, with caveats: changes to distributed tables occur on worker shards, so CDC setup differs from single-node Postgres
Capabilities
read · write · CDC

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.
How it works

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

    Choose tables

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

Citus and DealCloud 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 Citus and DealCloud.

Popular · 8 of 392
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