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Database ⇄ CRM

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

Keep AWS Aurora MySQL and Gladly in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

  • SOC 2 and 6 other compliance frameworks
  • POC with real engineers in minutes

Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect AWS Aurora MySQL and Gladly

Treat Gladly like part of your database: its records live in AWS Aurora MySQL as real tables, and writes in either place sync to the other in seconds.

Product and engineering teams constantly need CRM data, and the CRM API is a poor way to get it: rate limits, pagination, custom objects, and integration code that breaks when an admin renames a field. What they actually want is the data in AWS Aurora MySQL, where it can be queried and joined like everything else.

Stacksync mirrors Customer profiles, Conversations, Conversation items, Agents from Gladly into Rows, Columns, Primary keys and indexes, Views in AWS Aurora MySQL with real-time, bi-directional sync. Read CRM records with plain queries; write updates from your application and they appear in Gladly with validation intact. Go-to-market teams keep working in the CRM, engineers keep working in the database, and neither has to think about the other.

Common use cases

  • Keep customer attributes such as loyalty tier and lifetime value synced from a warehouse into Gladly profiles for routing and prioritization.
  • Push conversation outcomes into a CRM so account teams see support context on their accounts.
  • Stream row changes from Aurora into SaaS tools via binlog CDC instead of scheduled batch exports.
  • Sync a production Aurora cluster with an analytics database while filtering out sensitive columns.

Product events onto CRM records

Signup, usage, or lifecycle changes written to AWS Aurora MySQL sync onto the matching records in Gladly, giving go-to-market teams live product context.

Internal tools without API code

Back-office apps read and write the synced tables; Stacksync handles the Gladly API, limits, and retries.

Trigger workflows from CRM changes

Field and stage updates in Gladly arrive as row changes in AWS Aurora MySQL, ready to drive jobs and notifications.

What you can sync between AWS Aurora MySQL and Gladly

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 Gladly objects
Foreign keys Express relationships that syncs preserve when mapping to related objects elsewhere. Conversations Each customer's continuous timeline; status and outcomes sync to CRMs and warehouses.
Stored procedures and triggers Existing database logic keeps firing on rows written by a sync. Conversation items Individual messages across voice, SMS, chat, and email attached to the conversation.
Databases (schemas) Logical namespaces that scope which tables a sync connection can see. Agents User records used to attribute work in CX analytics.
Tables The primary sync unit; each table maps one-to-one to a table or object in the paired system. Topics Categorization applied to conversations; the key dimension for contact-driver reporting.
Rows Inserted, updated, and deleted individually or in bulk during two-way syncs. Tasks Follow-up work items created from external triggers or synced for workload reporting.
Columns MySQL data types are mapped to the paired system's field types during schema setup. Customer profiles The central entity; merges identifiers like email, phone, and order IDs, which syncs use for matching.
What ships with AWS Aurora MySQL ⇄ Gladly

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

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

Real-time

Two-way sync

Changes in AWS Aurora MySQL or Gladly 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 Gladly 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 Gladly record.

Observability

Monitoring

Track your AWS Aurora MySQL ⇄ Gladly 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 Gladly.

How the AWS Aurora MySQL and Gladly 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

Gladly

Integration surface
REST API
Authentication
API tokens used with basic authentication tied to an agent email
Change detection
Webhook event subscriptions for conversation and customer events, supplemented by polling and report exports
Capabilities
read · write · webhooks
Rate limits
Subject to the platform's API rate limits
How it works

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

    Choose tables

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

AWS Aurora MySQL and Gladly integration FAQ

SECURITY

Security teams love 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.

Learn more about security
SOC 2 type II
ISO 27001
HIPAA BAA
GDPR
CCPA
CSA STAR
DPF US-EU-UK-CH
→ 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 386 integrations available for AWS Aurora MySQL and Gladly.

Popular · 8 of 386
All AWS Aurora MySQL integrations All Gladly integrations Browse all integrations
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