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Data warehouse ⇄ Analytics

Databricks to Pendo integration — real-time, two-way sync

Keep Databricks and Pendo 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 Pendo

Put the same events, users, and metrics on both sides: Pendo and Databricks stay current in real time, in both directions.

Pendo is where teams explore, visualize, and report; Databricks is the store of record that holds the raw tables and full history behind those views. The two overlap wherever the same events, users, and metrics matter to both, and when the bridge between them is a nightly export or a hand-built extract, dashboards lag the warehouse and analysts spend the morning arguing over whose number is right.

Stacksync syncs Guide Events, Poll / NPS Responses, Features / Pages / Guides (metadata), Visitors in Pendo with Materialized Views, Volumes, SQL Warehouses, Change Data Feed in Databricks field by field, in real time, and in both directions. You decide which system owns which fields, and Stacksync resolves conflicts by rules you set. Whether the flow is warehouse tables feeding live reports or captured events and segments landing back in Databricks, every copy stays consistent.

Common use cases

  • 01 Sync Pendo Visitors and Accounts into a data model to score product-qualified accounts alongside behavioral event data.
  • 02 Load guide-engagement events into a reporting database to measure onboarding-flow adoption against retention and expansion.
  • 03 Serve ML feature outputs computed in Databricks to production apps through a synced operational store.
  • 04 Land CRM and ERP records in Delta tables continuously so lakehouse models work from current operational data.

Common sync patterns

Where Databricks holds the source tables: live data in the reporting layer

Records maintained in Databricks flow into Pendo as they change, so dashboards and reports read current rows rather than an overnight extract.

Where Pendo produces segments or scores: results back to the warehouse

Cohorts, segments, and computed metrics defined in Pendo write to Databricks as tables the rest of the stack can query and join.

Shared user and account keys

Users and accounts tracked in Pendo line up with the customer or user rows in Databricks on a stable key, so both sides count the same population.

What you can sync between Databricks and Pendo

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 Pendo objects How this pairing syncs
Volumes Unity Catalog file storage used for staging bulk loads. Visitors End-user records with agent-collected and custom fields; queried through the Aggregation API and enriched with custom fields written back via the Metadata API. Volumes is specific to Databricks and Visitors to Pendo — each maps to any object or custom field on the other side.
SQL Warehouses The compute endpoint a sync connects to for query execution. Accounts Company/workspace records that roll visitors up to an account dimension; readable via Aggregation and a write target for custom fields (plan, ARR, health) via the Metadata API. SQL Warehouses is specific to Databricks and Accounts to Pendo — 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. Feature Events Click/interaction events on tagged features, read-only through the Aggregation API over an event-time window and joined to the Feature definitions. Change Data Feed is specific to Databricks and Feature Events to Pendo — 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. Page Events Page-view events for tagged pages; read-only via the Aggregation API, used for adoption and path analysis in a warehouse. Catalogs is specific to Databricks and Page Events to Pendo — each maps to any object or custom field on the other side.
Schemas Group tables and views; syncs typically target a dedicated schema per source system. Guide Events Guide seen/advanced/dismissed and step events for in-app walkthroughs; read-only through the Aggregation API to measure onboarding flow adoption. Schemas is specific to Databricks and Guide Events to Pendo — each maps to any object or custom field on the other side.
Delta Tables The primary read and write target; operational data lands here as managed or external tables. Poll / NPS Responses Survey answers and NPS scores captured in-app (pollEvents / npsEvents); read-only via the Aggregation API as voice-of-customer data. Delta Tables is specific to Databricks and Poll / NPS Responses to Pendo — each maps to any object or custom field on the other side.

How changes propagate between Databricks and Pendo

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 Pendo 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 Pendo through its API, with automatic retries and rate-limit backoff.

Pendo Databricks Interval-based propagation

DetectionStacksync polls Pendo for changes on an incremental schedule, reading only records changed since the previous pass. Polling - reads query the Aggregation API over event-time windows.

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.
  • Pendo: Pendo does not publish fixed numeric limits; it throttles heavy Aggregation queries with 429s and caps/paginates large responses, so wide exports are paced and time-windowed.
What ships with Databricks ⇄ Pendo

Connect Databricks and Pendo for flexible, real-time data sync.

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

Real-time

Two-way sync

Changes in Databricks or Pendo instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Databricks or Pendo 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 Pendo record.

Observability

Monitoring

Track your Databricks ⇄ Pendo 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 Pendo.

How the Databricks and Pendo 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

Pendo

Integration surface
Pendo Engage API (REST) on app.pendo.io (US) / app.eu.pendo.io (EU), base path /api/v1/ - Aggregation API for reads and the Metadata API for writes
Authentication
Integration key sent in the x-pendo-integration-key header, generated in Subscription Settings; keys are scoped read-only or read/write, so writes require a read/write key
Change detection
Polling - reads query the Aggregation API over event-time windows; no change-data-capture feed and no data-change webhooks. Writes go through the Metadata API on demand.
Capabilities
read · write
Rate limits
Pendo does not publish fixed numeric limits; it throttles heavy Aggregation queries with 429s and caps/paginates large responses, so wide exports are paced and time-windowed.
How it works

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

    Choose tables

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

Databricks and Pendo 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.

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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 522 integrations available for Databricks and Pendo.

Popular · 8 of 522
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