Two-way sync
Changes in Amazon Aurora or IBM Netezza instantly reflect in both systems. No stale data, no manual imports.
Keep Amazon Aurora and IBM Netezza 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 Amazon Aurora's rows in IBM Netezza, 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 Amazon Aurora where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in Amazon Aurora sync into IBM Netezza in real time, and result tables in IBM Netezza sync back into Amazon Aurora, with schema and type mapping between the two systems handled for you.
Point analytical queries at the synced copy in IBM Netezza and keep Amazon Aurora focused on its operational workload.
Rows from Amazon Aurora land in IBM Netezza as they change, replacing hand-built CDC and batch extract jobs.
Aggregates or model outputs computed in IBM Netezza sync into Amazon Aurora, where whatever reads from that database gets them without querying the warehouse.
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.
| Amazon Aurora objects | IBM Netezza objects | |
|---|---|---|
| Read Replicas Reader endpoints that syncs can target to keep load off the writer. | Materialized views Precomputed results sometimes used as efficient read sources. | |
| Databases Logical databases within a cluster that scope a sync connection. | Sequences Key generators referenced when writing new rows. | |
| Schemas Namespaces (PostgreSQL) or database-level grouping (MySQL) used in table selection. | External tables File-backed load/unload paths used for bulk movement alongside row-level syncs. | |
| Tables Relational tables synced bi-directionally at row level. | Databases Top-level containers that scope a sync connection. | |
| Views Read-only query-backed sources for downstream syncs. | Schemas Namespace tables within a database. | |
| Materialized Views Precomputed result sets (PostgreSQL-compatible clusters) readable as sources. | Tables Distributed tables mapped directly to sync targets. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon Aurora–IBM Netezza connection.
Changes in Amazon Aurora or IBM Netezza instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Amazon Aurora or IBM Netezza data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Amazon Aurora or IBM Netezza record.
Track your Amazon Aurora ⇄ IBM Netezza sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Amazon Aurora and IBM Netezza.
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 Amazon Aurora and IBM Netezza 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 Amazon Aurora and IBM Netezza 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 Amazon Aurora and IBM Netezza: authenticate both systems, choose the objects to sync (such as Amazon Aurora's Read Replicas and Databases), map fields visually, and changes propagate both ways in milliseconds — no code required.
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 Amazon Aurora and IBM Netezza: Offload heavy reads; Operational data in the warehouse, minus the pipeline; Serve warehouse results at database speed. Point analytical queries at the synced copy in IBM Netezza and keep Amazon Aurora focused on its operational workload.
Amazon Aurora: MySQL or PostgreSQL wire protocol (SQL); optional RDS Data API over HTTPS. Authentication: Database credentials or IAM database authentication. IBM Netezza: SQL over JDBC/ODBC (Netezza's SQL dialect derives from PostgreSQL). Authentication: Database credentials. Stacksync manages authentication, retries, and rate limits on both sides.
IBM Netezza: There is no log-based CDC surface, so incremental extraction relies on timestamp columns or staging patterns. Amazon Aurora: Aurora separates compute from a shared distributed storage layer that keeps six copies of data across three Availability Zones. Stacksync's field mapping accounts for these differences between Amazon Aurora and IBM Netezza without custom code.
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 Amazon Aurora and IBM Netezza records are not retained after a sync operation.
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 Amazon Aurora and IBM Netezza.