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Data warehouse ⇄ Analytics

Apache Druid to Pendo integration — real-time, two-way sync

Keep Apache Druid 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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Why teams connect Apache Druid and Pendo

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

Pendo is where teams explore, visualize, and report; Apache Druid 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 Features / Pages / Guides (metadata), Visitors, Accounts, Feature Events in Pendo with Tasks, Datasources, Segments, Dimensions in Apache Druid 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 Apache Druid, every copy stays consistent.

Common use cases

  • 01 Set custom Visitor fields (role, lifecycle stage, entitlement) from the warehouse so in-app guides reach the right users without manual CSV uploads.
  • 02 Sync Pendo Visitors and Accounts into a data model to score product-qualified accounts alongside behavioral event data.
  • 03 Keep lookup tables in Druid refreshed from a CRM or database so query-time joins use current reference data.
  • 04 Expose product telemetry stored in Druid to business tools without granting direct cluster access.

Common sync patterns

One number both sides agree on

Metrics and aggregates stay aligned between the two systems, so a figure shown in Pendo matches the Apache Druid table it was built from instead of drifting between refreshes.

Where Apache Druid holds the source tables: live data in the reporting layer

Records maintained in Apache Druid 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 Apache Druid as tables the rest of the stack can query and join.

What you can sync between Apache Druid 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.

Apache Druid objects Pendo objects How this pairing syncs
Metrics Numeric columns, often pre-aggregated at ingestion via rollup. 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. Metrics is specific to Apache Druid and Accounts to Pendo — each maps to any object or custom field on the other side.
Ingestion Supervisors Long-running specs that pull from streams like Kafka; the write path into Druid. 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. Ingestion Supervisors is specific to Apache Druid and Feature Events to Pendo — each maps to any object or custom field on the other side.
Lookups Key-value mappings joined at query time, refreshable from external systems. Page Events Page-view events for tagged pages; read-only via the Aggregation API, used for adoption and path analysis in a warehouse. Lookups is specific to Apache Druid and Page Events to Pendo — each maps to any object or custom field on the other side.
Tasks Batch ingestion and compaction jobs monitored during data loads. Guide Events Guide seen/advanced/dismissed and step events for in-app walkthroughs; read-only through the Aggregation API to measure onboarding flow adoption. Tasks is specific to Apache Druid and Guide Events to Pendo — each maps to any object or custom field on the other side.
Datasources The table-like unit of storage and querying, the main target of reads and ingestion. Poll / NPS Responses Survey answers and NPS scores captured in-app (pollEvents / npsEvents); read-only via the Aggregation API as voice-of-customer data. Datasources is specific to Apache Druid and Poll / NPS Responses to Pendo — each maps to any object or custom field on the other side.
Segments Time-partitioned immutable files that hold datasource data; ingestion produces them. Features / Pages / Guides (metadata) Definitions of tagged UI elements listed through the entity endpoints; read-only reference used to label and join the event streams. Segments is specific to Apache Druid and Features / Pages / Guides (metadata) to Pendo — each maps to any object or custom field on the other side.

How changes propagate between Apache Druid 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.

Apache Druid Pendo Interval-based propagation

DetectionStacksync polls Apache Druid for changes on an incremental schedule, reading only records changed since the previous pass. Data enters Druid through streaming or batch ingestion rather than row updates.

DeliveryEach detected change is written to Pendo through its API, with automatic retries and rate-limit backoff.

Pendo Apache Druid 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 Apache Druid as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Apache Druid: No fixed API quotas; query concurrency is bounded by broker and historical node capacity.
  • 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 Apache Druid ⇄ Pendo

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Druid 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 Apache Druid or Pendo record.

Observability

Monitoring

Track your Apache Druid ⇄ Pendo sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Apache Druid and Pendo.

How the Apache Druid and Pendo connectors work

Apache Druid

Integration surface
REST API (SQL over HTTP and native JSON queries); JDBC via Avatica
Authentication
Deployment-dependent: basic authentication or an authenticator extension; often fronted by a proxy
Change detection
Not applicable for reads out (polling by time interval); data enters Druid through streaming or batch ingestion rather than row updates
Capabilities
read · write
Rate limits
No fixed API quotas; query concurrency is bounded by broker and historical node capacity

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 Apache Druid 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 Apache Druid 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
    Apache Druid connected
    Pendo connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

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

Apache Druid 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 412 integrations available for Apache Druid and Pendo.

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