Real-time
Two-way sync
Changes in DealCloud or TimescaleDB instantly reflect in both systems. No stale data, no manual imports.
CRM ⇄ Database
DealCloud to TimescaleDB integration — real-time, two-way sync
Keep DealCloud and TimescaleDB 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 TimescaleDB
Treat DealCloud like part of your database: its records live in TimescaleDB 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 TimescaleDB, where it can be queried and joined like everything else.
Stacksync mirrors Investment, Relationship, Activity, Task from DealCloud into Regular PostgreSQL Tables, Views, Schemas, Hypertables in TimescaleDB 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 Mirror DealCloud activities and tasks into an operational database to power internal dashboards without hitting the API on every read.
- 02 Push portfolio and fund performance data from a warehouse into DealCloud so dealmakers see up-to-date metrics on each investment.
- 03 Consolidate metrics from several services into one hypertable to serve a single reporting layer.
- 04 Sync product or IoT telemetry stored in TimescaleDB into a CRM so account teams see usage metrics next to the customer record.
Common sync patterns
Trigger workflows from CRM changes
Field and stage updates in DealCloud arrive as row changes in TimescaleDB, ready to drive jobs and notifications.
Query the CRM like a database
Accounts, contacts, and custom objects from DealCloud become tables in TimescaleDB you can join with application data directly.
Product events onto CRM records
Signup, usage, or lifecycle changes written to TimescaleDB sync onto the matching records in DealCloud, giving go-to-market teams live product context.
What you can sync between DealCloud and TimescaleDB
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 | TimescaleDB objects | How this pairing syncs | |
|---|---|---|---|
| Activity Synced with incremental and full sync. | Chunks Time-bounded partitions of a hypertable; syncs read and write through the parent hypertable and never address chunks directly. | Activity is specific to DealCloud and Chunks to TimescaleDB — each maps to any object or custom field on the other side. | |
| Task Synced with incremental and full sync. | Continuous Aggregates Incrementally maintained rollups that serve as pre-aggregated read sources for downstream systems. | Task is specific to DealCloud and Continuous Aggregates to TimescaleDB — each maps to any object or custom field on the other side. | |
| User Synced with incremental and full sync. | Regular PostgreSQL Tables Relational reference data such as devices, tenants, or accounts synced alongside the series data. | User is specific to DealCloud and Regular PostgreSQL Tables to TimescaleDB — each maps to any object or custom field on the other side. | |
| Deal Synced with incremental and full sync. | Views Standard SQL views used to shape or filter data for consumers. | Deal is specific to DealCloud and Views to TimescaleDB — each maps to any object or custom field on the other side. | |
| Company Synced with incremental and full sync. | Schemas Postgres namespaces used to separate synced datasets by team or environment. | Company is specific to DealCloud and Schemas to TimescaleDB — each maps to any object or custom field on the other side. | |
| Contact Synced with incremental and full sync. | Hypertables Time-partitioned tables that hold the main time-series data; the primary read and write target in syncs. | Contact is specific to DealCloud and Hypertables to TimescaleDB — each maps to any object or custom field on the other side. |
How changes propagate between DealCloud and TimescaleDB
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 TimescaleDB 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 TimescaleDB as a row-level write, with types converted between the two schemas.
TimescaleDB DealCloud Sub-second propagation
DetectionChanges in TimescaleDB are captured at the source via change data capture — no polling loop against its API. Log-based capture via PostgreSQL logical decoding where the deployment allows it — hypertable changes surface on the underlying chunk tables and must.
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.
- TimescaleDB: No API rate limits; throughput is bounded by database resources and connection limits.
What ships with DealCloud ⇄ TimescaleDB
Connect DealCloud and TimescaleDB for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every DealCloud–TimescaleDB connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever DealCloud or TimescaleDB 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 TimescaleDB record.
Observability
Monitoring
Track your DealCloud ⇄ TimescaleDB 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 TimescaleDB.
How the DealCloud and TimescaleDB 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.
TimescaleDB
- Integration surface
- SQL wire protocol (PostgreSQL)
- Authentication
- Database credentials
- Change detection
- Log-based capture via PostgreSQL logical decoding where the deployment allows it — hypertable changes surface on the underlying chunk tables and must be remapped to the parent — or timestamp-based polling on time columns; regular Postgres tables replicate through standard logical replication
- Capabilities
- read · write · CDC
- Rate limits
- No API rate limits; throughput is bounded by database resources and connection limits.
How it works
How to connect DealCloud to TimescaleDB — 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 TimescaleDB 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
TimescaleDB
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the DealCloud and TimescaleDB 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 ⇄ TimescaleDBCustomers 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 TimescaleDBCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
DealCloud and TimescaleDB integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between DealCloud and TimescaleDB: authenticate both systems, choose the objects to sync (such as DealCloud's Activity and Task), map fields visually, and changes propagate both ways in milliseconds — no code required.
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DealCloud: There is no universal native change-data-capture, so incremental sync relies on each entry's last-modified timestamp. TimescaleDB: Hypertables automatically partition rows into time-based chunks while inserts and queries target the parent table. Stacksync's field mapping accounts for these differences between DealCloud and TimescaleDB without custom code.
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Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means DealCloud and TimescaleDB records are not retained after a sync operation.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed DealCloud and TimescaleDB connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom DealCloud–TimescaleDB integration in-house.
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Yes — Stacksync ships production-grade connectors for both DealCloud and TimescaleDB. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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Change detection on DealCloud: Incremental via each entry's last-modified timestamp; DealCloud has no universal native change-data-capture, so Stacksync polls modified rows on an interval. On TimescaleDB: Log-based capture via PostgreSQL logical decoding where the deployment allows it — hypertable changes surface on the underlying chunk tables and must be remapped to the parent — or timestamp-based polling on time columns; regular Postgres tables replicate through standard logical replication. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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:
Related integrations
Every pair below is a real-time, two-way sync. Search all 392 integrations available for DealCloud and TimescaleDB.
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TimescaleDB ⇄ Affinity -
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