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Data warehouse

Greenplum to Materialize integration — real-time, two-way sync

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.

  • SOC 2 and 6 other compliance frameworks
  • POC with real engineers in minutes

Adopted by fast-scaling companies moving mission-critical data in real time

Case study
Migrated from MuleSoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
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Migrated from Fivetran
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Migrated from Celigo
Why teams connect Greenplum and Materialize

Keep tables consistent across Greenplum and Materialize, for a migration, a multi-warehouse stack, or a dataset two platforms both need.

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.

Common use cases

  • 01 Consolidate data from multiple source systems into partitioned Greenplum fact tables.
  • 02 Load operational data from CRMs, ERPs, and production databases into Greenplum for MPP analytics.
  • 03 Drive alerting and operational tooling from SUBSCRIBE change streams instead of scheduled queries.
  • 04 Maintain real-time inventory, usage, or account-health counters consumed by customer-facing applications.

Common sync patterns

Consolidation after M&A

Bring the acquired company's warehouse data across continuously instead of through one-off dumps.

Migration without a big bang

When one platform is replacing the other, keep tables mirrored while workloads move over gradually, and cut over with nothing to backfill.

Serve tools that only connect to one platform

Mirror the datasets a BI tool, notebook, or application needs onto the platform it can actually reach.

What you can sync between Greenplum and Materialize

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 How this pairing syncs
Tables Heap or append-optimized tables mapped directly to sync targets. Tables User-managed tables that accept INSERT/UPDATE/DELETE from sync pipelines. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Schemas Namespace tables and control which objects a sync can see. Schemas & Databases Namespaces that organize objects a sync targets. Schemas is specific to Greenplum and Schemas & Databases to Materialize — each maps to any object or custom field on the other side.
Partitions Large tables are commonly partitioned by date, which shapes incremental reads. Sources Ingestion points (Kafka, Postgres CDC, MySQL CDC, webhook) that feed external data into Materialize. Partitions is specific to Greenplum and Sources to Materialize — each maps to any object or custom field on the other side.
Views Read-only projections used to shape data before syncing it out. Materialized Views Incrementally maintained query results that syncs read as continuously up-to-date datasets. Views is specific to Greenplum and Materialized Views to Materialize — each maps to any object or custom field on the other side.
External tables Reference external files for bulk load paths alongside row-level syncs. Sinks Outbound connections that emit view changes to Kafka topics. External tables is specific to Greenplum and Sinks to Materialize — each maps to any object or custom field on the other side.
Rows Read and written by key; distribution keys determine where rows live. Indexes In-memory arrangements that make view reads fast for serving workloads. Rows is specific to Greenplum and Indexes to Materialize — each maps to any object or custom field on the other side.

How changes propagate between Greenplum and Materialize

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.

Greenplum Materialize Interval-based propagation

DetectionStacksync polls Greenplum for changes on an incremental schedule, reading only records changed since the previous pass. Polling with timestamp or key-based cursors.

DeliveryEach detected change is applied to Materialize as a row-level write, with types converted between the two schemas.

Materialize Greenplum Sub-second propagation

DetectionChanges in Materialize are captured at the source via change data capture — no polling loop against its API. SUBSCRIBE queries stream row-level changes of any view or table to the client.

DeliveryEach detected change is applied to Greenplum as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Greenplum: Bounded by cluster resources and concurrency settings rather than an API quota.
What ships with Greenplum ⇄ Materialize

Connect Greenplum and Materialize for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Greenplum–Materialize connection.

Real-time

Two-way sync

Changes in Greenplum or Materialize instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Greenplum or Materialize 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 Greenplum or Materialize record.

Observability

Monitoring

Track your Greenplum ⇄ Materialize sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Greenplum and Materialize.

How the Greenplum and Materialize connectors work

Greenplum

Integration surface
PostgreSQL wire protocol (libpq), plus JDBC/ODBC drivers
Authentication
Database credentials
Change detection
Polling with timestamp or key-based cursors; Greenplum does not expose logical-decoding CDC
Capabilities
read · write
Rate limits
Bounded by cluster resources and concurrency settings rather than an API quota.

Materialize

Integration surface
PostgreSQL wire protocol (SQL)
Authentication
Database credentials (username/password; app passwords in the managed cloud service)
Change detection
SUBSCRIBE queries stream row-level changes of any view or table to the client
Capabilities
read · write · CDC
How it works

How to connect Greenplum to Materialize — 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.

  1. 01

    Connect your apps

    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.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Greenplum connected
    Materialize connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    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.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Greenplum ⇄ Materialize
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Greenplum Materialize
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Greenplum and Materialize integration FAQ

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.

Learn more about security
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:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 371 integrations available for Greenplum and Materialize.

Popular · 3 of 371
All Greenplum integrations All Materialize integrations Browse all integrations
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