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AI ⇄ Database

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

Keep Autopilot and AWS Aurora MySQL 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 Autopilot and AWS Aurora MySQL

Sync the records in AWS Aurora MySQL into Autopilot and land its embeddings, classifications, and generated fields back on the same rows, in real time and without a pipeline to maintain.

AI systems do not hold customers or invoices the way business apps do. What they hold is derived from your data: the vectors and metadata in a vector store, or the classifications, extracted fields, and generated text a model produces over records it was given. AWS Aurora MySQL is where those source records actually live. The bridge between the two is the row itself, since an item in Autopilot and the record in AWS Aurora MySQL it describes are two halves of the same thing, and they drift the moment one is updated without the other.

Stacksync syncs Columns, Primary keys and indexes, Views, Foreign keys in AWS Aurora MySQL with Journeys (Triggers), Activities, Contacts, Lists in Autopilot in real time. Rows created or changed in AWS Aurora MySQL flow into Autopilot so inference and embedding run on current data, and the scores, labels, and generated fields Autopilot produces flow back onto the matching rows in AWS Aurora MySQL, mapped field by field. A change on either side appears on the other within seconds, with no extraction job or webhook plumbing to keep alive.

Because matching is by a stable identifier, every row in AWS Aurora MySQL stays tied to its AI-side counterpart in Autopilot. Retrieval, enrichment, and generated content always resolve back to the record they came from, so there are no orphaned vectors and no labels describing a version of a row that no longer exists.

Common use cases

  • 01 Upsert Contacts from a CRM or product database into Autopilot so new signups and profile changes flow into email and SMS journeys without manual CSV imports.
  • 02 Add contacts to a Journey from a database event or CRM stage change to start automated onboarding or nurture sequences.
  • 03 Sync a production Aurora cluster with an analytics database while filtering out sensitive columns.
  • 04 Let operations teams edit records in a spreadsheet-style tool with changes written back to Aurora safely.

Common sync patterns

Run the AI on current data

Rows created or changed in AWS Aurora MySQL flow into Autopilot as they happen, so embeddings, classifications, and prompts run on the latest records instead of a nightly snapshot.

Write results back onto the record

Scores, labels, extracted fields, or generated text produced in Autopilot land on the matching row in AWS Aurora MySQL, next to the source data your applications already query.

Keep derived data fresh as sources change

When a row in AWS Aurora MySQL is updated or removed, its counterpart in Autopilot is updated or removed too, so nothing in Autopilot describes a record that has since changed or gone.

What you can sync between Autopilot and AWS Aurora MySQL

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.

Autopilot objects AWS Aurora MySQL objects How this pairing syncs
Custom Fields User-defined contact properties (string, number, date, boolean); discovered so field keys map cleanly to destination columns. Stored procedures and triggers Existing database logic keeps firing on rows written by a sync. Custom Fields is specific to Autopilot and Stored procedures and triggers to AWS Aurora MySQL — each maps to any object or custom field on the other side.
Smart Segments Rule-based dynamic audiences; membership is computed by Autopilot, so it is read-only over the API. Databases (schemas) Logical namespaces that scope which tables a sync connection can see. Smart Segments is specific to Autopilot and Databases (schemas) to AWS Aurora MySQL — each maps to any object or custom field on the other side.
Journeys (Triggers) Automation journeys; a contact can be added to a journey via its trigger endpoint to start automated email or SMS sequences. Tables The primary sync unit; each table maps one-to-one to a table or object in the paired system. Journeys (Triggers) is specific to Autopilot and Tables to AWS Aurora MySQL — each maps to any object or custom field on the other side.
Activities Per-contact activity and event history (opens, clicks, journey steps); read-only feed used for engagement reporting. Rows Inserted, updated, and deleted individually or in bulk during two-way syncs. Activities is specific to Autopilot and Rows to AWS Aurora MySQL — each maps to any object or custom field on the other side.
Contacts Core people records (email, name, custom fields, list and segment membership); upserted two-way as the primary sync object. Columns MySQL data types are mapped to the paired system's field types during schema setup. Contacts is specific to Autopilot and Columns to AWS Aurora MySQL — each maps to any object or custom field on the other side.
Lists Static contact lists; membership is readable per list and writable by adding or removing contacts. Primary keys and indexes Used to match rows across systems and keep incremental syncs efficient. Lists is specific to Autopilot and Primary keys and indexes to AWS Aurora MySQL — each maps to any object or custom field on the other side.

How changes propagate between Autopilot and AWS Aurora MySQL

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.

Autopilot AWS Aurora MySQL Interval-based propagation

DetectionStacksync polls Autopilot for changes on an incremental schedule, reading only records changed since the previous pass. No CDC.

DeliveryEach detected change is applied to AWS Aurora MySQL as a row-level write, with types converted between the two schemas.

AWS Aurora MySQL Autopilot 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 Autopilot through its API, with automatic retries and rate-limit backoff.

Rate-limit considerations

  • Autopilot: The REST API is capped at 100 requests/minute per account; exceeding it returns HTTP 429. Enterprise plans can request a higher limit. Contact writes accept an array for bulk upsert, and list and segment reads paginate via a bookmark cursor.
What ships with Autopilot ⇄ AWS Aurora MySQL

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

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

Observability

Monitoring

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

Trading partners

EDI

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

How the Autopilot and AWS Aurora MySQL connectors work

Autopilot

Integration surface
REST API (Autopilot v1); Autopilot rebranded to Ortto in 2021 and the newer Ortto API co-exists with the legacy Autopilot endpoints
Authentication
Per-account API key sent in the autopilotapikey request header (generated in account settings); requests use Content-Type application/json against https://api2.autopilothq.com/v1/
Change detection
No CDC; incremental sync polls the /contacts endpoint with bookmark cursor pagination and updated timestamps. Journey webhook actions can push specific contact events, but there is no general change-subscription webhook, so polling is the reliable path.
Capabilities
read · write
Rate limits
The REST API is capped at 100 requests/minute per account; exceeding it returns HTTP 429. Enterprise plans can request a higher limit. Contact writes accept an array for bulk upsert, and list and segment reads paginate via a bookmark cursor.
Autopilot setup guide

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
How it works

How to connect Autopilot to AWS Aurora MySQL — 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 Autopilot and AWS Aurora MySQL 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
    Autopilot connected
    AWS Aurora MySQL connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

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

Autopilot and AWS Aurora MySQL 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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→ 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:

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 423 integrations available for Autopilot and AWS Aurora MySQL.

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