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Database ⇄ AI

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

Keep Amazon Aurora and Autopilot 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 Amazon Aurora and Autopilot

Sync the records in Amazon Aurora 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. Amazon Aurora 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 Amazon Aurora it describes are two halves of the same thing, and they drift the moment one is updated without the other.

Stacksync syncs Tables, Views, Materialized Views, Columns and Data Types in Amazon Aurora with Custom Fields, Smart Segments, Journeys (Triggers), Activities in Autopilot in real time. Rows created or changed in Amazon Aurora 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 Amazon Aurora, 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 Amazon Aurora 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 Stream row-level changes from Aurora into a warehouse for near-real-time analytics without batch exports.
  • 04 Consolidate several Aurora clusters into one reporting database.

Common sync patterns

One record, one identifier

Each item in Autopilot carries the key of the row in Amazon Aurora it came from, so results resolve back to the exact record with nothing orphaned or duplicated.

Run the AI on current data

Rows created or changed in Amazon Aurora 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 Amazon Aurora, next to the source data your applications already query.

What you can sync between Amazon Aurora and Autopilot

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.

Amazon Aurora objects Autopilot objects How this pairing syncs
Materialized Views Precomputed result sets (PostgreSQL-compatible clusters) readable as sources. Journeys (Triggers) Automation journeys; a contact can be added to a journey via its trigger endpoint to start automated email or SMS sequences. Materialized Views is specific to Amazon Aurora and Journeys (Triggers) to Autopilot — each maps to any object or custom field on the other side.
Columns and Data Types Standard MySQL or PostgreSQL types mapped during field mapping. Activities Per-contact activity and event history (opens, clicks, journey steps); read-only feed used for engagement reporting. Columns and Data Types is specific to Amazon Aurora and Activities to Autopilot — each maps to any object or custom field on the other side.
Primary and Foreign Keys Constraints used to identify records and preserve relational integrity in syncs. Contacts Core people records (email, name, custom fields, list and segment membership); upserted two-way as the primary sync object. Primary and Foreign Keys is specific to Amazon Aurora and Contacts to Autopilot — each maps to any object or custom field on the other side.
Read Replicas Reader endpoints that syncs can target to keep load off the writer. Lists Static contact lists; membership is readable per list and writable by adding or removing contacts. Read Replicas is specific to Amazon Aurora and Lists to Autopilot — each maps to any object or custom field on the other side.
Databases Logical databases within a cluster that scope a sync connection. Custom Fields User-defined contact properties (string, number, date, boolean); discovered so field keys map cleanly to destination columns. Databases is specific to Amazon Aurora and Custom Fields to Autopilot — each maps to any object or custom field on the other side.
Schemas Namespaces (PostgreSQL) or database-level grouping (MySQL) used in table selection. Smart Segments Rule-based dynamic audiences; membership is computed by Autopilot, so it is read-only over the API. Schemas is specific to Amazon Aurora and Smart Segments to Autopilot — each maps to any object or custom field on the other side.

How changes propagate between Amazon Aurora and Autopilot

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.

Amazon Aurora Autopilot Sub-second propagation

DetectionChanges in Amazon Aurora are captured at the source via change data capture — no polling loop against its API. Log-based CDC: binlog on MySQL-compatible clusters, logical replication/decoding on PostgreSQL-compatible clusters.

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

Autopilot Amazon Aurora 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 Amazon Aurora as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Amazon Aurora: No API rate limits for wire-protocol access; throughput is bounded by instance class and connection limits.
  • 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 Amazon Aurora ⇄ Autopilot

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Amazon Aurora or Autopilot 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 Amazon Aurora or Autopilot record.

Observability

Monitoring

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

Trading partners

EDI

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

How the Amazon Aurora and Autopilot connectors work

Amazon Aurora

Integration surface
MySQL or PostgreSQL wire protocol (SQL); optional RDS Data API over HTTPS
Authentication
Database credentials or IAM database authentication
Change detection
Log-based CDC: binlog on MySQL-compatible clusters, logical replication/decoding on PostgreSQL-compatible clusters; polling as a fallback
Capabilities
read · write · CDC
Rate limits
No API rate limits for wire-protocol access; throughput is bounded by instance class and connection limits

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
How it works

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

    Choose tables

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

Amazon Aurora and Autopilot 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 407 integrations available for Amazon Aurora and Autopilot.

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