Real-time
Two-way sync
Changes in AWS Aurora MySQL or Starburst Enterprise instantly reflect in both systems. No stale data, no manual imports.
Database ⇄ Data warehouse
AWS Aurora MySQL to Starburst Enterprise integration — real-time, two-way sync
Keep AWS Aurora MySQL and Starburst Enterprise 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 Starburst Enterprise
Connect AWS Aurora MySQL and Starburst Enterprise 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 Starburst Enterprise, 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 Starburst Enterprise in real time, and result tables in Starburst Enterprise sync back into AWS Aurora MySQL, with schema and type mapping between the two systems handled for you.
Common use cases
- 01 Write curated or reconciled results back to lakehouse tables through connectors that support inserts
- 02 Read federated views that join warehouse, lake, and database tables, then sync the result into operational tools like a CRM
- 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
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 Starburst Enterprise 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 Starburst Enterprise as they change, replacing hand-built CDC and batch extract jobs.
What you can sync between AWS Aurora MySQL and Starburst Enterprise
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 | Starburst Enterprise 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. | Tables Queryable relations; writes pass through to sources whose connectors support them. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Columns MySQL data types are mapped to the paired system's field types during schema setup. | Columns Typed per the Trino type system, mapped from each source's native types. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Views Can serve as read-only sync sources for derived or filtered datasets. | Views Engine-level SQL views used to shape federated data before syncing it out. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Foreign keys Express relationships that syncs preserve when mapping to related objects elsewhere. | Catalogs Each catalog maps to a connector (Iceberg, Hive, PostgreSQL, and others) exposing an external source. | Foreign keys is specific to AWS Aurora MySQL and Catalogs to Starburst Enterprise — each maps to any object or custom field on the other side. | |
| Stored procedures and triggers Existing database logic keeps firing on rows written by a sync. | Schemas Namespaces within a catalog, mirroring the underlying source's databases or schemas. | Stored procedures and triggers is specific to AWS Aurora MySQL and Schemas to Starburst Enterprise — each maps to any object or custom field on the other side. | |
| Databases (schemas) Logical namespaces that scope which tables a sync connection can see. | Materialized views Precomputed results that make repeated sync reads cheaper. | Databases (schemas) is specific to AWS Aurora MySQL and Materialized views to Starburst Enterprise — each maps to any object or custom field on the other side. |
How changes propagate between AWS Aurora MySQL and Starburst Enterprise
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 Starburst Enterprise 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 applied to Starburst Enterprise as a row-level write, with types converted between the two schemas.
Starburst Enterprise AWS Aurora MySQL Interval-based propagation
DetectionStacksync polls Starburst Enterprise for changes on an incremental schedule, reading only records changed since the previous pass. Query-based polling.
DeliveryEach detected change is applied to AWS Aurora MySQL as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- Starburst Enterprise: Throughput is governed by cluster sizing and resource groups rather than API quotas.
What ships with AWS Aurora MySQL ⇄ Starburst Enterprise
Connect AWS Aurora MySQL and Starburst Enterprise for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS Aurora MySQL–Starburst Enterprise connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever AWS Aurora MySQL or Starburst Enterprise 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 Starburst Enterprise record.
Observability
Monitoring
Track your AWS Aurora MySQL ⇄ Starburst Enterprise 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 Starburst Enterprise.
How the AWS Aurora MySQL and Starburst Enterprise 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
Starburst Enterprise
- Integration surface
- ANSI SQL over JDBC/ODBC drivers and the Trino client REST protocol
- Authentication
- Deployment-dependent: username/password, LDAP, OAuth 2.0, or Kerberos
- Change detection
- Query-based polling; Starburst is a query engine and exposes no change log of its own
- Capabilities
- read · write
- Rate limits
- Throughput is governed by cluster sizing and resource groups rather than API quotas
How it works
How to connect AWS Aurora MySQL to Starburst Enterprise — 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.
- 01
Connect your apps
Authenticate AWS Aurora MySQL and Starburst Enterprise with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
AWS Aurora MySQL
connected
Starburst Enterprise
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the AWS Aurora MySQL and Starburst Enterprise 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.
objects · AWS Aurora MySQL ⇄ Starburst EnterpriseCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
AWS Aurora MySQL Starburst EnterpriseCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
AWS Aurora MySQL and Starburst Enterprise integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between AWS Aurora MySQL and Starburst Enterprise: authenticate both systems, choose the objects to sync (such as AWS Aurora MySQL's Tables and Columns), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Starburst Enterprise: A single SQL statement can join tables across catalogs, meaning one query can span several distinct backend systems. AWS Aurora MySQL: Aurora MySQL is wire-compatible with MySQL, so any standard MySQL driver, ORM, or CDC tooling works without modification. Stacksync's field mapping accounts for these differences between AWS Aurora MySQL and Starburst Enterprise without custom code.
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Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means AWS Aurora MySQL and Starburst Enterprise records are not retained after a sync operation.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed AWS Aurora MySQL and Starburst Enterprise connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom AWS Aurora MySQL–Starburst Enterprise integration in-house.
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Yes — Stacksync ships production-grade connectors for both AWS Aurora MySQL and Starburst Enterprise. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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Change detection on AWS Aurora MySQL: Log-based CDC via the MySQL binary log (binlog), with polling on timestamp columns as a fallback. On Starburst Enterprise: Query-based polling; Starburst is a query engine and exposes no change log of its own. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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.
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
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 382 integrations available for AWS Aurora MySQL and Starburst Enterprise.
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