Real-time
Two-way sync
Changes in Databricks or Gainsight instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ Business productivity
Databricks to Gainsight integration — real-time, two-way sync
Keep Databricks and Gainsight 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 Databricks and Gainsight
Get the data locked inside Gainsight into Databricks as live tables, and send results back where Gainsight can use them, without writing a pipeline.
Whatever Gainsight is used for, it accumulates data the rest of the company wants to analyze, and that data usually sits behind an API rather than in the warehouse. Building and babysitting an extraction pipeline is the tax most teams pay for it.
Stacksync syncs Company, Person (People), Relationship, CTA (Call to Action) from Gainsight into tables in Databricks continuously, handling schema, rate limits, and retries. Because the sync is bi-directional, results computed in Databricks can also be written back into fields in Gainsight where the tool can use them.
Common use cases
- 01 Read Timeline Activities and Success Plan objectives into a reporting database for churn, QBR, and CSM-productivity dashboards.
- 02 Keep Relationship records aligned with a billing system or ERP so multi-product customers map to the correct contracts and invoices.
- 03 Land CRM and ERP records in Delta tables continuously so lakehouse models work from current operational data.
- 04 Use Change Data Feed to propagate only changed rows to downstream apps instead of full-table scans.
Common sync patterns
Where Gainsight accepts updates: operational write-back
Segments, scores, or reference values computed in Databricks sync back onto records in Gainsight, putting analysis where the work happens.
History that outlives the tool
A continuously synced copy in Databricks preserves a queryable record even as data ages out of Gainsight or gets changed inside it.
Analytics on Gainsight's data
Records and events from Gainsight land in Databricks as queryable tables, current within seconds and ready to join with the rest of the warehouse.
What you can sync between Databricks and Gainsight
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.
| Databricks objects | Gainsight objects | How this pairing syncs | |
|---|---|---|---|
| Views Curated read-only projections used as sync sources for downstream tools. | Timeline Activity Logged calls, emails, and notes; usually read out into a reporting database for QBR and churn analysis. | Views is specific to Databricks and Timeline Activity to Gainsight — each maps to any object or custom field on the other side. | |
| Materialized Views Precomputed results read on a schedule for reverse-ETL style syncs. | Success Plan Account objectives with associated tasks; read out for reporting or synced with project tools tracking onboarding and adoption. | Materialized Views is specific to Databricks and Success Plan to Gainsight — each maps to any object or custom field on the other side. | |
| Volumes Unity Catalog file storage used for staging bulk loads. | Task and Playbook Cockpit tasks generated from CTAs and playbooks; synced with Jira or Asana so execution happens in the team's own tool. | Volumes is specific to Databricks and Task and Playbook to Gainsight — each maps to any object or custom field on the other side. | |
| SQL Warehouses The compute endpoint a sync connects to for query execution. | Custom Objects Org-specific MDA tables with the __gc suffix; discoverable via the Describe API so field mappings can be generated automatically. | SQL Warehouses is specific to Databricks and Custom Objects to Gainsight — each maps to any object or custom field on the other side. | |
| Change Data Feed Row-level change records on Delta tables that drive incremental reads. | Company Customer/account master in Gainsight CS; two-way synced with CRM and warehouse customer tables to keep ARR, owner, and renewal fields aligned. | Change Data Feed is specific to Databricks and Company to Gainsight — each maps to any object or custom field on the other side. | |
| Catalogs Top level of the Unity Catalog namespace, scoping which schemas a sync can address. | Person (People) Contacts associated to companies through the Company Person junction; synced two-way with CRM contacts and warehouse person records. | Catalogs is specific to Databricks and Person (People) to Gainsight — each maps to any object or custom field on the other side. |
How changes propagate between Databricks and Gainsight
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.
Databricks Gainsight Sub-second propagation
DetectionChanges in Databricks are captured at the source via change data capture — no polling loop against its API. Delta Lake Change Data Feed for row-level changes.
DeliveryEach detected change is written to Gainsight through its API, with automatic retries and rate-limit backoff.
Gainsight Databricks Interval-based propagation
DetectionStacksync polls Gainsight for changes on an incremental schedule, reading only records changed since the previous pass. Polling on the ModifiedDate (GS Modified Date) system field, which is filterable and sortable on every object.
DeliveryEach detected change is applied to Databricks as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- Databricks: Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits.
- Gainsight: Synchronous APIs are capped near 100 calls/min and 50,000/day; the asynchronous Bulk API allows 10 calls/hour and 100/day. Both are fixed-window limits, and the applicable per-hour and per-day limits are returned in the x-ratelimit-limit response header.
What ships with Databricks ⇄ Gainsight
Connect Databricks and Gainsight for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Databricks–Gainsight connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Databricks or Gainsight 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 Databricks or Gainsight record.
Observability
Monitoring
Track your Databricks ⇄ Gainsight sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Databricks and Gainsight.
How the Databricks and Gainsight connectors work
Databricks
- Integration surface
- SQL over JDBC/ODBC via SQL warehouses, plus a REST API including statement execution
- Authentication
- Personal access tokens or OAuth machine-to-machine credentials for service principals
- Change detection
- Delta Lake Change Data Feed for row-level changes; otherwise incremental polling on watermark columns
- Capabilities
- read · write · CDC
- Rate limits
- Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits
Gainsight
- Integration surface
- REST APIs (per-object) and asynchronous Bulk REST API
- Authentication
- API access key passed in the 'accesskey' request header (non-expiring), generated by a Gainsight admin; M2M OAuth (Client ID/Secret) is also supported
- Change detection
- Polling on the ModifiedDate (GS Modified Date) system field, which is filterable and sortable on every object; Rules Engine Real-Time Rules can optionally push specific object events (e.g., a Company stage change) to an external endpoint
- Capabilities
- read · write
- Rate limits
- Synchronous APIs are capped near 100 calls/min and 50,000/day; the asynchronous Bulk API allows 10 calls/hour and 100/day. Both are fixed-window limits, and the applicable per-hour and per-day limits are returned in the x-ratelimit-limit response header.
How it works
How to connect Databricks to Gainsight — 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 Databricks and Gainsight with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Databricks
connected
Gainsight
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Databricks and Gainsight 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 · Databricks ⇄ GainsightCustomers 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.
Databricks GainsightCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Databricks and Gainsight integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Databricks and Gainsight: authenticate both systems, choose the objects to sync (such as Databricks's Views and Materialized Views), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed Databricks and Gainsight connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Databricks–Gainsight integration in-house.
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Yes — Stacksync ships production-grade connectors for both Databricks and Gainsight. 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 Databricks: Delta Lake Change Data Feed for row-level changes; otherwise incremental polling on watermark columns. On Gainsight: Polling on the ModifiedDate (GS Modified Date) system field, which is filterable and sortable on every object; Rules Engine Real-Time Rules can optionally push specific object events (e.g., a Company stage change) to an external endpoint. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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On the Gainsight side: Company, Person (People), Relationship, CTA (Call to Action), plus custom fields where Gainsight exposes them. On the Databricks side: Volumes, SQL Warehouses, Change Data Feed, Catalogs. 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.
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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