Two-way sync
Changes in AWS S3 or Greenplum instantly reflect in both systems. No stale data, no manual imports.
Keep AWS S3 and Greenplum in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Companies end up with two warehouses for practical reasons: a migration in progress, teams that standardized on different platforms, an acquisition, or tools that only connect to one of them. The result is the same dataset maintained twice, with duplicated pipelines and numbers that almost match.
Stacksync syncs tables between AWS S3 and Greenplum continuously, in either or both directions. Rows changed on one platform appear on the other within seconds, with schema and type mapping handled, so both warehouses answer questions with the same data.
Mirror the datasets a BI tool, notebook, or application needs onto the platform it can actually reach.
Where different teams run different warehouses, sync the curated tables both rely on so their metrics agree by construction.
Bring the acquired company's warehouse data across continuously instead of through one-off dumps.
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 S3 objects | Greenplum objects | |
|---|---|---|
| Buckets Top-level containers a sync targets; region and policy are set at this level. | Views Read-only projections used to shape data before syncing it out. | |
| Objects The stored files (CSV, JSON, Parquet); syncs read them as datasets or write exports into them. | External tables Reference external files for bulk load paths alongside row-level syncs. | |
| Prefixes Key-name paths used to partition synced datasets, since S3 has no real directories. | Rows Read and written by key; distribution keys determine where rows live. | |
| Object Metadata System and user-defined metadata read alongside object contents. | Databases Top-level containers that scope a sync connection. | |
| Object Versions Prior copies retained when versioning is enabled, relevant for reprocessing. | Schemas Namespace tables and control which objects a sync can see. | |
| Event Notifications Notifications on object creation or deletion that trigger incremental processing. | Tables Heap or append-optimized tables mapped directly to sync targets. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS S3–Greenplum connection.
Changes in AWS S3 or Greenplum instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever AWS S3 or Greenplum data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single AWS S3 or Greenplum record.
Track your AWS S3 ⇄ Greenplum sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between AWS S3 and Greenplum.
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 AWS S3 and Greenplum 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 AWS S3 and Greenplum 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 AWS S3 and Greenplum: authenticate both systems, choose the objects to sync (such as AWS S3's Buckets and Objects), map fields visually, and changes propagate both ways in milliseconds — no code required.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed AWS S3 and Greenplum connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom AWS S3–Greenplum integration in-house.
Yes — Stacksync ships production-grade connectors for both AWS S3 and Greenplum. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
Change detection on AWS S3: S3 Event Notifications on object create/delete delivered to SQS, SNS, Lambda, or EventBridge; list-based polling as a fallback. On Greenplum: Polling with timestamp or key-based cursors; Greenplum does not expose logical-decoding CDC. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the AWS S3 side: Multipart Uploads, Buckets, Objects, Prefixes, plus custom fields where AWS S3 exposes them. On the Greenplum side: Databases, Schemas, Tables, Partitions. 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.
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 AWS S3 and Greenplum.