Real-time
Two-way sync
Changes in Actian Vector or Vitally instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ CRM
Actian Vector to Vitally integration — real-time, two-way sync
Keep Actian Vector and Vitally 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
Case study
Migrated from MuleSoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Actian Vector and Vitally
Sync Vitally into Actian Vector continuously and push warehouse results back onto CRM records, one two-way connection instead of two pipelines.
The CRM feeds the warehouse and the warehouse should feed the CRM: relationship data flows one way, and computed scores, segments, and customer context flow back. Most teams build the first half as a batch pipeline and never quite get to the second.
Stacksync does both with one connection. Custom Trait, Account, User, Organization from Vitally land in Actian Vector as live tables, updated within seconds, and columns computed in Actian Vector write back to fields in Vitally. There is no separate ETL and reverse-ETL stack to stitch together and no jobs to babysit.
Common use cases
- 01 Keep CS tasks and notes aligned between Vitally and ticketing or project tools.
- 02 Sync account health scores and lifecycle stages from Vitally into a CRM so sales sees churn risk before renewals.
- 03 Keep reporting tables in Vector refreshed from production databases on a schedule.
- 04 Publish aggregates computed in Vector back to operational tools that business teams use.
Common sync patterns
A single customer view
Join Vitally's relationship data with billing, product, and support data in Actian Vector to build the customer picture the CRM alone cannot hold.
Cleanup that sticks
Deduplication and normalization done in Actian Vector can be written back, so warehouse-side cleanup actually fixes the CRM.
CRM analytics on live data
Accounts, contacts, and activity from Vitally are queryable in Actian Vector moments after they change, so dashboards stop lagging the reality they describe.
What you can sync between Actian Vector and Vitally
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.
| Actian Vector objects | Vitally objects | How this pairing syncs | |
|---|---|---|---|
| Users and Roles Database principals used to grant the sync connection least-privilege access. | NPS Response NPS survey responses for account-health reporting. | Users and Roles is specific to Actian Vector and NPS Response to Vitally — each maps to any object or custom field on the other side. | |
| Databases Top-level containers targeted by a sync connection. | Custom Trait Custom account and user traits for segmentation. | Databases is specific to Actian Vector and Custom Trait to Vitally — each maps to any object or custom field on the other side. | |
| Schemas Namespaces used to organize synced tables. | Account Core customer account records with health scores and lifecycle traits; created, updated, retrieved, and listed via the REST API. | Schemas is specific to Actian Vector and Account to Vitally — each maps to any object or custom field on the other side. | |
| Tables Columnar tables that serve as sync sources or destinations. | User End users tied to accounts, including activity and custom traits. | Tables is specific to Actian Vector and User to Vitally — each maps to any object or custom field on the other side. | |
| Views SQL views readable as query-backed sync sources. | Organization Parent organizations for hierarchical B2B account structures. | Views is specific to Actian Vector and Organization to Vitally — each maps to any object or custom field on the other side. | |
| Columns Typed columns mapped field-by-field during schema mapping. | Task CS tasks and follow-ups, readable and writable for workflow sync. | Columns is specific to Actian Vector and Task to Vitally — each maps to any object or custom field on the other side. |
How changes propagate between Actian Vector and Vitally
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.
Actian Vector Vitally Interval-based propagation
DetectionStacksync polls Actian Vector for changes on an incremental schedule, reading only records changed since the previous pass. Polling on timestamp or key columns.
DeliveryEach detected change is written to Vitally through its API, with automatic retries and rate-limit backoff.
Vitally Actian Vector Sub-second propagation
DetectionVitally notifies Stacksync of record changes through webhook events. Incremental polling on updatedAt cursors.
DeliveryEach detected change is applied to Actian Vector as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- Actian Vector: No API rate limits in the SaaS sense; throughput depends on cluster resources and query concurrency.
- Vitally: Default rate limit of 1,000 requests/min (token bucket); write operations consume more budget, headers expose remaining quota.
What ships with Actian Vector ⇄ Vitally
Connect Actian Vector and Vitally for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Actian Vector–Vitally connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Actian Vector or Vitally 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 Actian Vector or Vitally record.
Observability
Monitoring
Track your Actian Vector ⇄ Vitally sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Actian Vector and Vitally.
How the Actian Vector and Vitally connectors work
Actian Vector
- Integration surface
- SQL over JDBC/ODBC
- Authentication
- Database credentials
- Change detection
- Polling on timestamp or key columns; no log-based CDC interface is generally exposed to external consumers
- Capabilities
- read · write
- Rate limits
- No API rate limits in the SaaS sense; throughput depends on cluster resources and query concurrency
Vitally
- Integration surface
- REST API with cursor-based pagination (sortable by createdAt/updatedAt)
- Authentication
- API key via Basic Auth; keys created in Settings -> Integrations -> REST API and individually revocable
- Change detection
- Incremental polling on updatedAt cursors; playbook-triggered webhooks can push events for near real-time updates
- Capabilities
- read · write · webhooks
- Rate limits
- Default rate limit of 1,000 requests/min (token bucket); write operations consume more budget, headers expose remaining quota.
How it works
How to connect Actian Vector to Vitally — 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 Actian Vector and Vitally with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Actian Vector
connected
Vitally
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Actian Vector and Vitally 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 · Actian Vector ⇄ VitallyCustomers 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.
Actian Vector VitallyCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Actian Vector and Vitally integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Actian Vector and Vitally: authenticate both systems, choose the objects to sync (such as Actian Vector's Users and Roles and Databases), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Vitally: No native change-data-capture stream; incremental sync relies on updatedAt-sorted cursor pagination. Actian Vector: Actian Vector is a columnar analytics database with vectorized query execution, so it is used as an analytical destination rather than a transactional source. Stacksync's field mapping accounts for these differences between Actian Vector and Vitally 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 Actian Vector and Vitally 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 Actian Vector and Vitally connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Actian Vector–Vitally integration in-house.
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Yes — Stacksync ships production-grade connectors for both Actian Vector and Vitally. 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 Actian Vector: Polling on timestamp or key columns; no log-based CDC interface is generally exposed to external consumers. On Vitally: Incremental polling on updatedAt cursors; playbook-triggered webhooks can push events for near real-time updates. 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
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