Real-time
Two-way sync
Changes in Actian Vector or AWS Aurora MySQL instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ Database
Actian Vector to AWS Aurora MySQL integration — real-time, two-way sync
Keep Actian Vector and AWS Aurora MySQL 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 Actian Vector and AWS Aurora MySQL
Connect AWS Aurora MySQL and Actian Vector 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 Actian Vector, 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 Actian Vector in real time, and result tables in Actian Vector sync back into AWS Aurora MySQL, with schema and type mapping between the two systems handled for you.
Common use cases
- 01 Consolidate data from several source systems into one Vector database for BI dashboards.
- 02 Load operational data from CRMs and ERPs into Actian Vector tables for analytical queries.
- 03 Stream row changes from Aurora into SaaS tools via binlog CDC instead of scheduled batch exports.
- 04 Sync a production Aurora cluster with an analytics database while filtering out sensitive columns.
Common sync patterns
Operational data in the warehouse, minus the pipeline
Rows from AWS Aurora MySQL land in Actian Vector as they change, replacing hand-built CDC and batch extract jobs.
Serve warehouse results at database speed
Aggregates or model outputs computed in Actian Vector sync into AWS Aurora MySQL, where whatever reads from that database gets them without querying the warehouse.
Fresh analytics without loading windows
Because changes stream continuously, analysts query current data instead of waiting for last night's load.
What you can sync between Actian Vector and AWS Aurora MySQL
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.
| Actian Vector objects | AWS Aurora MySQL objects | How this pairing syncs | |
|---|---|---|---|
| Tables Columnar tables that serve as sync sources or destinations. | Tables The primary sync unit; each table maps one-to-one to a table or object in the paired system. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Views SQL views readable as query-backed sync sources. | Views Can serve as read-only sync sources for derived or filtered datasets. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Columns Typed columns mapped field-by-field during schema mapping. | Columns MySQL data types are mapped to the paired system's field types during schema setup. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Schemas Namespaces used to organize synced tables. | Databases (schemas) Logical namespaces that scope which tables a sync connection can see. | Schemas is specific to Actian Vector and Databases (schemas) to AWS Aurora MySQL — each maps to any object or custom field on the other side. | |
| Users and Roles Database principals used to grant the sync connection least-privilege access. | Rows Inserted, updated, and deleted individually or in bulk during two-way syncs. | Users and Roles is specific to Actian Vector and Rows to AWS Aurora MySQL — each maps to any object or custom field on the other side. | |
| Databases Top-level containers targeted by a sync connection. | Primary keys and indexes Used to match rows across systems and keep incremental syncs efficient. | Databases is specific to Actian Vector and Primary keys and indexes to AWS Aurora MySQL — each maps to any object or custom field on the other side. |
How changes propagate between Actian Vector and AWS Aurora MySQL
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.
Actian Vector AWS Aurora MySQL Interval-based propagation
DetectionStacksync polls Actian Vector for changes on an incremental schedule, reading only records changed since the previous pass. Polling on timestamp or key columns.
DeliveryEach detected change is applied to AWS Aurora MySQL as a row-level write, with types converted between the two schemas.
AWS Aurora MySQL Actian Vector 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 Actian Vector as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- Actian Vector: No API rate limits in the SaaS sense; throughput depends on cluster resources and query concurrency.
What ships with Actian Vector ⇄ AWS Aurora MySQL
Connect Actian Vector and AWS Aurora MySQL for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Actian Vector–AWS Aurora MySQL connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Actian Vector or AWS Aurora MySQL 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 Actian Vector or AWS Aurora MySQL record.
Observability
Monitoring
Track your Actian Vector ⇄ AWS Aurora MySQL sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Actian Vector and AWS Aurora MySQL.
How the Actian Vector and AWS Aurora MySQL connectors work
Actian Vector
- Integration surface
- SQL over JDBC/ODBC
- Authentication
- Database credentials
- Change detection
- Polling on timestamp or key columns; no log-based CDC interface is generally exposed to external consumers
- Capabilities
- read · write
- Rate limits
- No API rate limits in the SaaS sense; throughput depends on cluster resources and query concurrency
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
How it works
How to connect Actian Vector to AWS Aurora MySQL — 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 Actian Vector and AWS Aurora MySQL with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Actian Vector
connected
AWS Aurora MySQL
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Actian Vector and AWS Aurora MySQL 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 · Actian Vector ⇄ AWS Aurora MySQLCustomers 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.
Actian Vector AWS Aurora MySQLCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Actian Vector and AWS Aurora MySQL integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Actian Vector and AWS Aurora MySQL: authenticate both systems, choose the objects to sync (such as Actian Vector's Tables and Views), map fields visually, and changes propagate both ways in milliseconds — no code required.
-
Common patterns for Actian Vector and AWS Aurora MySQL: Operational data in the warehouse, minus the pipeline; Serve warehouse results at database speed; Fresh analytics without loading windows. Rows from AWS Aurora MySQL land in Actian Vector as they change, replacing hand-built CDC and batch extract jobs.
-
Actian Vector: SQL over JDBC/ODBC. Authentication: Database credentials. AWS Aurora MySQL: SQL wire protocol (MySQL-compatible), standard MySQL drivers and JDBC. Authentication: Database credentials, optionally AWS IAM database authentication, over TLS. Stacksync manages authentication, retries, and rate limits on both sides.
-
Actian Vector: Access is through standard SQL over JDBC/ODBC connectivity, which means syncs interact with ordinary tables, views, and schemas. AWS Aurora MySQL: Binlog-based CDC requires binary logging to be enabled through the cluster parameter group; once on, changes can be captured without querying production tables. Stacksync's field mapping accounts for these differences between Actian Vector and AWS Aurora MySQL 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 Actian Vector and AWS Aurora MySQL 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 Actian Vector and AWS Aurora MySQL connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Actian Vector–AWS Aurora MySQL integration in-house.
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
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