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Database ⇄ Data warehouse

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

Keep AWS Aurora MySQL and Firebolt 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 Firebolt

Connect AWS Aurora MySQL and Firebolt with one live, two-way sync: operational rows flow into the warehouse, and computed results flow back where systems can read them fast.

Operational databases and analytical warehouses want the same data at different moments. Analysts want AWS Aurora MySQL's rows in Firebolt, current and joinable, without a change-data-capture pipeline to maintain. Engineers want the outputs of warehouse work, such as aggregates, features, and segments, available in AWS Aurora MySQL where the services that read from it get them at normal query latency.

Stacksync covers both directions with one connection. Tables or collections in AWS Aurora MySQL sync into Firebolt in real time, and result tables in Firebolt sync back into AWS Aurora MySQL, with schema and type mapping between the two systems handled for you.

Common use cases

  • Sync CRM objects into Firebolt so customer-facing dashboards reflect recent pipeline changes.
  • Keep dimension tables aligned with source systems while high-volume event data loads through separate batch pipelines.
  • Let operations teams edit records in a spreadsheet-style tool with changes written back to Aurora safely.
  • Give backend services read and write access to ERP or billing data by syncing it into Aurora tables the application already queries.

Fresh analytics without loading windows

Because changes stream continuously, analysts query current data instead of waiting for last night's load.

Offload heavy reads

Point analytical queries at the synced copy in Firebolt and keep AWS Aurora MySQL focused on its operational workload.

Operational data in the warehouse, minus the pipeline

Rows from AWS Aurora MySQL land in Firebolt as they change, replacing hand-built CDC and batch extract jobs.

What you can sync between AWS Aurora MySQL and Firebolt

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 Firebolt objects
Stored procedures and triggers Existing database logic keeps firing on rows written by a sync. Engines Compute resources that must be running for a sync to read or write.
Databases (schemas) Logical namespaces that scope which tables a sync connection can see. Databases Logical containers holding the tables a sync targets.
Tables The primary sync unit; each table maps one-to-one to a table or object in the paired system. Tables Managed columnar tables written with SQL; the main sync destination.
Rows Inserted, updated, and deleted individually or in bulk during two-way syncs. External tables References to files in object storage used to stage bulk loads.
Columns MySQL data types are mapped to the paired system's field types during schema setup. Views Curated query surfaces commonly used as sources for reverse ETL.
Primary keys and indexes Used to match rows across systems and keep incremental syncs efficient. Aggregating indexes Precomputed rollups maintained at write time; incremental loads update them automatically.
What ships with AWS Aurora MySQL ⇄ Firebolt

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

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

Real-time

Two-way sync

Changes in AWS Aurora MySQL or Firebolt 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 Firebolt 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 Firebolt record.

Observability

Monitoring

Track your AWS Aurora MySQL ⇄ Firebolt 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 Firebolt.

How the AWS Aurora MySQL and Firebolt 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

Firebolt

Integration surface
SQL over a REST API, with JDBC, Python, and Node.js SDKs
Authentication
Service account credentials (client ID and secret) exchanged for OAuth 2.0 tokens
Change detection
Polling; Firebolt is an analytics destination and does not expose a change feed
Capabilities
read · write
Rate limits
No fixed request quota; throughput depends on the engine size attached to the workload
How it works

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

    Choose tables

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

AWS Aurora MySQL and Firebolt 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.

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:

Related integrations

Every pair below is a real-time, two-way sync. Search all 386 integrations available for AWS Aurora MySQL and Firebolt.

Popular · 8 of 386
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