Two-way sync
Changes in Actian Vector or AWS Aurora PostgreSQL instantly reflect in both systems. No stale data, no manual imports.
Keep Actian Vector and AWS Aurora PostgreSQL in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Operational databases and analytical warehouses want the same data at different moments. Analysts want AWS Aurora PostgreSQL'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 PostgreSQL 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 PostgreSQL sync into Actian Vector in real time, and result tables in Actian Vector sync back into AWS Aurora PostgreSQL, with schema and type mapping between the two systems handled for you.
Rows from AWS Aurora PostgreSQL land in Actian Vector as they change, replacing hand-built CDC and batch extract jobs.
Aggregates or model outputs computed in Actian Vector sync into AWS Aurora PostgreSQL, where whatever reads from that database gets them without querying the warehouse.
Because changes stream continuously, analysts query current data instead of waiting for last night's load.
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 PostgreSQL objects | |
|---|---|---|
| Tables Columnar tables that serve as sync sources or destinations. | Replication slots and publications The logical replication objects that power log-based CDC. | |
| Views SQL views readable as query-backed sync sources. | Databases and schemas PostgreSQL's two-level namespace scopes which tables a sync connection targets. | |
| Columns Typed columns mapped field-by-field during schema mapping. | Tables The core sync unit; rows are matched across systems by primary key. | |
| Users and Roles Database principals used to grant the sync connection least-privilege access. | Rows Inserted, updated, and deleted in both directions during bi-directional syncs. | |
| Databases Top-level containers targeted by a sync connection. | Columns Rich Postgres types including JSONB and arrays are mapped to the paired system's fields. | |
| Schemas Namespaces used to organize synced tables. | Primary keys and constraints Identify rows for upserts and enforce integrity on sync writes. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Actian Vector–AWS Aurora PostgreSQL connection.
Changes in Actian Vector or AWS Aurora PostgreSQL instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Actian Vector or AWS Aurora PostgreSQL data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Actian Vector or AWS Aurora PostgreSQL record.
Track your Actian Vector ⇄ AWS Aurora PostgreSQL sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Actian Vector and AWS Aurora PostgreSQL.
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.
Authenticate Actian Vector and AWS Aurora PostgreSQL with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Pick the Actian Vector and AWS Aurora PostgreSQL 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.
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Yes. Stacksync provides a managed, real-time two-way integration between Actian Vector and AWS Aurora PostgreSQL: 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.
On the Actian Vector side: Views, Columns, Users and Roles, Databases, plus custom fields where Actian Vector exposes them. On the AWS Aurora PostgreSQL side: Databases and schemas, Tables, Rows, Columns. Stacksync auto-detects both schemas and converts types between the two systems.
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 Actian Vector and AWS Aurora PostgreSQL: Operational data in the warehouse, minus the pipeline; Serve warehouse results at database speed; Fresh analytics without loading windows. Rows from AWS Aurora PostgreSQL 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 PostgreSQL: SQL wire protocol (PostgreSQL-compatible), standard Postgres 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: Actian Vector is a columnar analytics database with vectorized query execution, so it is used as an analytical destination rather than a transactional source. AWS Aurora PostgreSQL: Aurora's storage layer replicates data six ways across three Availability Zones and is shared by up to 15 read replicas. Stacksync's field mapping accounts for these differences between Actian Vector and AWS Aurora PostgreSQL without custom code.
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.
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Securely connects to your systems with:
Every pair below is a real-time, two-way sync. Search all 386 integrations available for Actian Vector and AWS Aurora PostgreSQL.