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Database ⇄ Analytics

AWS Aurora MySQL to Pendo integration — real-time, two-way sync

Keep AWS Aurora MySQL 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 AWS Aurora MySQL and Pendo

Give Pendo the users, events, and records that live in AWS Aurora MySQL in real time, and sync the cohorts and scores Pendo computes back into AWS Aurora MySQL where your applications read them.

A database holds the rows your business runs on: the users, events, orders, and records that every service reads and writes. Pendo is where people make sense of them, as dashboards, funnels, cohorts, and metrics. Moving the data from AWS Aurora MySQL into Pendo usually means a hand-built extract or a change-data-capture pipeline that breaks the moment a column is renamed, and reporting that always trails last night's load.

Stacksync syncs Views, Foreign keys, Stored procedures and triggers, Databases (schemas) in AWS Aurora MySQL with Feature Events, Page Events, Guide Events, Poll / NPS Responses in Pendo in real time and in both directions. Operational rows flow into Pendo as they change, so dashboards read current data with no pipeline to maintain, and the segments, cohorts, or scores Pendo computes flow back into AWS Aurora MySQL, where the applications and services that read from it get them at normal query latency. Field-level mapping, schema and type translation, and conflict resolution are handled for you.

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 Let operations teams edit records in a spreadsheet-style tool with changes written back to Aurora safely.
  • 04 Give backend services read and write access to ERP or billing data by syncing it into Aurora tables the application already queries.

Common sync patterns

Where Pendo builds cohorts or scores: results your services can read

Segments, cohorts, or scores computed in Pendo sync back into AWS Aurora MySQL, where the services that read from the database act on them at query speed without calling the analytics API.

Analytics on live operational data, minus the pipeline

The users, events, orders, and records stored in AWS Aurora MySQL land in Pendo as they change, so dashboards, funnels, and metrics run on current data instead of last night's extract.

One version of each user or account

A user, account, or record corrected in either system updates the other, so the identity your reports group by matches the identity your database stores.

What you can sync between AWS Aurora MySQL 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.

AWS Aurora MySQL objects Pendo objects How this pairing syncs
Tables The primary sync unit; each table maps one-to-one to a table or object in the paired system. 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. Tables is specific to AWS Aurora MySQL and Features / Pages / Guides (metadata) to Pendo — each maps to any object or custom field on the other side.
Rows Inserted, updated, and deleted individually or in bulk during two-way syncs. 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. Rows is specific to AWS Aurora MySQL and Visitors to Pendo — each maps to any object or custom field on the other side.
Columns MySQL data types are mapped to the paired system's field types during schema setup. 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. Columns is specific to AWS Aurora MySQL and Accounts to Pendo — each maps to any object or custom field on the other side.
Primary keys and indexes Used to match rows across systems and keep incremental syncs efficient. 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. Primary keys and indexes is specific to AWS Aurora MySQL and Feature Events to Pendo — each maps to any object or custom field on the other side.
Views Can serve as read-only sync sources for derived or filtered datasets. Page Events Page-view events for tagged pages; read-only via the Aggregation API, used for adoption and path analysis in a warehouse. Views is specific to AWS Aurora MySQL and Page Events to Pendo — each maps to any object or custom field on the other side.
Foreign keys Express relationships that syncs preserve when mapping to related objects elsewhere. Guide Events Guide seen/advanced/dismissed and step events for in-app walkthroughs; read-only through the Aggregation API to measure onboarding flow adoption. Foreign keys is specific to AWS Aurora MySQL and Guide Events to Pendo — each maps to any object or custom field on the other side.

How changes propagate between AWS Aurora MySQL 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.

AWS Aurora MySQL Pendo Sub-second propagation

DetectionChanges in AWS Aurora MySQL are captured at the source via change data capture — no polling loop against its API. Log-based CDC via the MySQL binary log (binlog), with polling on timestamp columns as a fallback.

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

Pendo AWS Aurora MySQL 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 AWS Aurora MySQL as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • 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 AWS Aurora MySQL ⇄ Pendo

Connect AWS Aurora MySQL and Pendo for flexible, real-time data sync.

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever AWS Aurora MySQL 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 AWS Aurora MySQL or Pendo record.

Observability

Monitoring

Track your AWS Aurora MySQL ⇄ Pendo sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between AWS Aurora MySQL and Pendo.

How the AWS Aurora MySQL and Pendo connectors work

AWS Aurora MySQL

Integration surface
SQL wire protocol (MySQL-compatible), standard MySQL drivers and JDBC
Authentication
Database credentials, optionally AWS IAM database authentication, over TLS
Change detection
Log-based CDC via the MySQL binary log (binlog), with polling on timestamp columns as a fallback
Capabilities
read · write · CDC

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 AWS Aurora MySQL 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 AWS Aurora MySQL 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
    AWS Aurora MySQL connected
    Pendo connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the AWS Aurora MySQL 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 · AWS Aurora MySQL ⇄ 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
    AWS Aurora MySQL Pendo
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

AWS Aurora MySQL 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 422 integrations available for AWS Aurora MySQL and Pendo.

Popular · 7 of 422
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