Two-way sync
Changes in Greenplum or Materialize instantly reflect in both systems. No stale data, no manual imports.
Keep Greenplum and Materialize 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 Greenplum and Materialize 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.
Bring the acquired company's warehouse data across continuously instead of through one-off dumps.
When one platform is replacing the other, keep tables mirrored while workloads move over gradually, and cut over with nothing to backfill.
Mirror the datasets a BI tool, notebook, or application needs onto the platform it can actually reach.
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.
| Greenplum objects | Materialize objects | |
|---|---|---|
| Rows Read and written by key; distribution keys determine where rows live. | Sinks Outbound connections that emit view changes to Kafka topics. | |
| Databases Top-level containers that scope a sync connection. | Indexes In-memory arrangements that make view reads fast for serving workloads. | |
| Schemas Namespace tables and control which objects a sync can see. | Clusters Compute pools that isolate ingestion, view maintenance, and serving. | |
| Tables Heap or append-optimized tables mapped directly to sync targets. | Connections & Secrets Stored credentials and endpoints used by sources and sinks. | |
| Partitions Large tables are commonly partitioned by date, which shapes incremental reads. | Schemas & Databases Namespaces that organize objects a sync targets. | |
| Views Read-only projections used to shape data before syncing it out. | Tables User-managed tables that accept INSERT/UPDATE/DELETE from sync pipelines. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Greenplum–Materialize connection.
Changes in Greenplum or Materialize instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Greenplum or Materialize data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Greenplum or Materialize record.
Track your Greenplum ⇄ Materialize sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Greenplum and Materialize.
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 Greenplum and Materialize 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 Greenplum and Materialize 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 Greenplum and Materialize: authenticate both systems, choose the objects to sync (such as Greenplum's Rows and Databases), 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 Greenplum and Materialize connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Greenplum–Materialize integration in-house.
Yes — Stacksync ships production-grade connectors for both Greenplum and Materialize. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
Change detection on Greenplum: Polling with timestamp or key-based cursors; Greenplum does not expose logical-decoding CDC. On Materialize: SUBSCRIBE queries stream row-level changes of any view or table to the client. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Greenplum side: Rows, Databases, Schemas, Tables, plus custom fields where Greenplum exposes them. On the Materialize side: Schemas & Databases, Tables, Sources, Materialized Views. 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 Greenplum and Materialize.