Real-time
Two-way sync
Changes in DealCloud or DuckDB instantly reflect in both systems. No stale data, no manual imports.
CRM ⇄ Database
DealCloud to DuckDB integration — real-time, two-way sync
Keep DealCloud and DuckDB 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 DealCloud and DuckDB
Treat DealCloud like part of your database: its records live in DuckDB 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 DuckDB, where it can be queried and joined like everything else.
Stacksync mirrors Deal, Company, Contact, Fund from DealCloud into Schemas, Tables, Views, External files (Parquet/CSV/JSON) in DuckDB 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 Use DuckDB as a transform step: read synced Parquet exports, aggregate with SQL, and write results back to an operational database.
- 04 Sync SaaS data to Parquet on object storage and query it with DuckDB without standing up a warehouse.
Common sync patterns
Query the CRM like a database
Accounts, contacts, and custom objects from DealCloud become tables in DuckDB you can join with application data directly.
Product events onto CRM records
Signup, usage, or lifecycle changes written to DuckDB 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 DealCloud and DuckDB
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 | DuckDB objects | How this pairing syncs | |
|---|---|---|---|
| Fund Synced with incremental and full sync. | Database files Single-file .duckdb databases that jobs read and write directly on disk or object storage. | Fund is specific to DealCloud and Database files to DuckDB — each maps to any object or custom field on the other side. | |
| Investment Synced with incremental and full sync. | Schemas Namespaces within a database used to organize tables in sync outputs. | Investment is specific to DealCloud and Schemas to DuckDB — each maps to any object or custom field on the other side. | |
| Relationship Synced with incremental and full sync. | Tables Columnar tables created via SQL; the destination for materialized sync data. | Relationship is specific to DealCloud and Tables to DuckDB — each maps to any object or custom field on the other side. | |
| Activity Synced with incremental and full sync. | Views SQL views used to shape or filter data for downstream consumers. | Activity is specific to DealCloud and Views to DuckDB — each maps to any object or custom field on the other side. | |
| Task Synced with incremental and full sync. | External files (Parquet/CSV/JSON) Files DuckDB queries in place without loading, common as a sync interchange format. | Task is specific to DealCloud and External files (Parquet/CSV/JSON) to DuckDB — each maps to any object or custom field on the other side. | |
| User Synced with incremental and full sync. | Attached databases Additional database files or external systems attached into one session for cross-source queries. | User is specific to DealCloud and Attached databases to DuckDB — each maps to any object or custom field on the other side. |
How changes propagate between DealCloud and DuckDB
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 DuckDB 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 DuckDB as a row-level write, with types converted between the two schemas.
DuckDB DealCloud Interval-based propagation
DetectionStacksync polls DuckDB for changes on an incremental schedule, reading only records changed since the previous pass. Polling or full re-reads.
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.
- DuckDB: No API rate limits; throughput is bounded by local compute and I/O.
What ships with DealCloud ⇄ DuckDB
Connect DealCloud and DuckDB for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every DealCloud–DuckDB connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever DealCloud or DuckDB 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 DuckDB record.
Observability
Monitoring
Track your DealCloud ⇄ DuckDB 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 DuckDB.
How the DealCloud and DuckDB 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.
DuckDB
- Integration surface
- In-process SQL engine via client libraries (Python, Node.js, JDBC, CLI); no server or network API by default
- Authentication
- None built in; access control is file-system level (MotherDuck adds token auth for its hosted service)
- Change detection
- Polling or full re-reads; no change feed or transaction log API
- Capabilities
- read · write
- Rate limits
- No API rate limits; throughput is bounded by local compute and I/O
How it works
How to connect DealCloud to DuckDB — 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.
- 01
Connect your apps
Authenticate DealCloud and DuckDB with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
DealCloud
connected
DuckDB
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the DealCloud and DuckDB 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.
objects · DealCloud ⇄ DuckDBCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
DealCloud DuckDBCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
DealCloud and DuckDB integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between DealCloud and DuckDB: authenticate both systems, choose the objects to sync (such as DealCloud's Fund and Investment), map fields visually, and changes propagate both ways in milliseconds — no code required.
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On the DealCloud side: Deal, Company, Contact, Fund, plus custom fields where DealCloud exposes them. On the DuckDB side: Schemas, Tables, Views, External files (Parquet/CSV/JSON). Stacksync auto-detects both schemas and converts types between the two systems.
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Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
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Common patterns for DealCloud and DuckDB: Query the CRM like a database; Product events onto CRM records; Internal tools without API code. Accounts, contacts, and custom objects from DealCloud become tables in DuckDB you can join with application data directly.
-
DealCloud: 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. DuckDB: In-process SQL engine via client libraries (Python, Node.js, JDBC, CLI); no server or network API by default. Authentication: None built in; access control is file-system level (MotherDuck adds token auth for its hosted service). Stacksync manages authentication, retries, and rate limits on both sides.
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DealCloud: DealCloud's data model is fully configurable: each firm defines its own entry types (objects) and fields, so syncs map to a firm-specific schema rather than a fixed one. DuckDB: Concurrency is single-writer: one process holds write access to a database file at a time, which shapes how sync jobs schedule writes. Stacksync's field mapping accounts for these differences between DealCloud and DuckDB without custom code.
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.
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:
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