Real-time
Two-way sync
Changes in AWS Aurora MySQL or SingleStore instantly reflect in both systems. No stale data, no manual imports.
Database
AWS Aurora MySQL to SingleStore integration — real-time, two-way sync
Keep AWS Aurora MySQL and SingleStore 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
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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 SingleStore
Keep AWS Aurora MySQL and SingleStore synchronized in real time, across engines, regions, or services, in one or both directions.
Two databases that must agree is one of the oldest problems in engineering: different engines for different workloads, separate services with overlapping reference data, a migration in flight, or regional instances that share a subset of records. Hand-rolled replication across systems means change capture, conflict handling, and type mapping, all built and maintained by your team.
Stacksync syncs tables or collections between AWS Aurora MySQL and SingleStore continuously and bi-directionally, translating types between the two engines and resolving conflicts by rules you configure. Rows written on either side appear on the other within seconds.
Common use cases
- 01 Let operations teams edit records in a spreadsheet-style tool with changes written back to Aurora safely.
- 02 Give backend services read and write access to ERP or billing data by syncing it into Aurora tables the application already queries.
- 03 Consolidate data from transactional databases and SaaS apps into one store that handles both lookups and scans.
- 04 Keep reference data consistent between SingleStore and application databases.
Common sync patterns
Cross-engine sync
Keep the same dataset live in both AWS Aurora MySQL and SingleStore, so each workload runs on the engine that suits it.
Migration with zero-downtime cutover
When one database is replacing the other, sync both directions during the transition and switch traffic when ready, without a freeze window.
Shared reference data between services
Services that own separate databases stay consistent on the records they share, without a custom replication layer.
What you can sync between AWS Aurora MySQL and SingleStore
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 | SingleStore objects | How this pairing syncs | |
|---|---|---|---|
| Views Can serve as read-only sync sources for derived or filtered datasets. | Views Read-only projections used as curated sync sources. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Databases (schemas) Logical namespaces that scope which tables a sync connection can see. | Pipelines Native ingestion jobs from Kafka or object storage that coexist with external syncs. | Databases (schemas) is specific to AWS Aurora MySQL and Pipelines to SingleStore — each maps to any object or custom field on the other side. | |
| Tables The primary sync unit; each table maps one-to-one to a table or object in the paired system. | Stored Procedures Existing logic sometimes invoked on write paths. | Tables is specific to AWS Aurora MySQL and Stored Procedures to SingleStore — each maps to any object or custom field on the other side. | |
| Rows Inserted, updated, and deleted individually or in bulk during two-way syncs. | Indexes and Shard Keys Determine data distribution and lookup speed for sync match keys. | Rows is specific to AWS Aurora MySQL and Indexes and Shard Keys to SingleStore — each maps to any object or custom field on the other side. | |
| Columns MySQL data types are mapped to the paired system's field types during schema setup. | Databases The connection target containing the tables a sync addresses. | Columns is specific to AWS Aurora MySQL and Databases to SingleStore — each maps to any object or custom field on the other side. | |
| Primary keys and indexes Used to match rows across systems and keep incremental syncs efficient. | Tables (rowstore and columnstore) Primary read/write target; storage type affects whether a table suits point lookups or scans. | Primary keys and indexes is specific to AWS Aurora MySQL and Tables (rowstore and columnstore) to SingleStore — each maps to any object or custom field on the other side. |
How changes propagate between AWS Aurora MySQL and SingleStore
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 SingleStore 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 SingleStore as a row-level write, with types converted between the two schemas.
SingleStore AWS Aurora MySQL Interval-based propagation
DetectionStacksync polls SingleStore for changes on an incremental schedule, reading only records changed since the previous pass. Polling on timestamp or watermark columns.
DeliveryEach detected change is applied to AWS Aurora MySQL as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- SingleStore: No API rate limits; throughput is bounded by workspace or cluster size.
What ships with AWS Aurora MySQL ⇄ SingleStore
Connect AWS Aurora MySQL and SingleStore for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS Aurora MySQL–SingleStore connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever AWS Aurora MySQL or SingleStore 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 SingleStore record.
Observability
Monitoring
Track your AWS Aurora MySQL ⇄ SingleStore 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 SingleStore.
How the AWS Aurora MySQL and SingleStore 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
SingleStore
- Integration surface
- SQL over the MySQL wire protocol; an HTTP Data API is also available for SQL over REST
- Authentication
- Database credentials
- Change detection
- Polling on timestamp or watermark columns; the platform also provides change-observation features in recent versions
- Capabilities
- read · write
- Rate limits
- No API rate limits; throughput is bounded by workspace or cluster size
How it works
How to connect AWS Aurora MySQL to SingleStore — 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 SingleStore 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
SingleStore
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the AWS Aurora MySQL and SingleStore 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 ⇄ SingleStoreCustomers 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 SingleStoreCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
AWS Aurora MySQL and SingleStore integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between AWS Aurora MySQL and SingleStore: authenticate both systems, choose the objects to sync (such as AWS Aurora MySQL's Views and Databases (schemas)), map fields visually, and changes propagate both ways in milliseconds — no code required.
-
Yes — Stacksync ships production-grade connectors for both AWS Aurora MySQL and SingleStore. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
-
Change detection on AWS Aurora MySQL: Log-based CDC via the MySQL binary log (binlog), with polling on timestamp columns as a fallback. On SingleStore: Polling on timestamp or watermark columns; the platform also provides change-observation features in recent versions. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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On the AWS Aurora MySQL side: Foreign keys, Stored procedures and triggers, Databases (schemas), Tables, plus custom fields where AWS Aurora MySQL exposes them. On the SingleStore side: Databases, Tables (rowstore and columnstore), Views, Reference Tables. Stacksync auto-detects both schemas and converts types between the two systems.
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Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
-
Common patterns for AWS Aurora MySQL and SingleStore: Cross-engine sync; Migration with zero-downtime cutover; Shared reference data between services. Keep the same dataset live in both AWS Aurora MySQL and SingleStore, so each workload runs on the engine that suits it.
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 393 integrations available for AWS Aurora MySQL and SingleStore.
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