Real-time
Two-way sync
Changes in Citus or Materialize instantly reflect in both systems. No stale data, no manual imports.
Database ⇄ Data warehouse
Citus to Materialize integration — real-time, two-way sync
Keep Citus 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
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Citus and Materialize
Connect Citus and Materialize with one live, two-way sync: operational rows flow into the warehouse, and computed results flow back where systems can read them fast.
Operational databases and analytical warehouses want the same data at different moments. Analysts want Citus's rows in Materialize, 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 Citus where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in Citus sync into Materialize in real time, and result tables in Materialize sync back into Citus, with schema and type mapping between the two systems handled for you.
Common use cases
- 01 Read computed view results back into a CRM or application database as derived fields.
- 02 Drive alerting and operational tooling from SUBSCRIBE change streams instead of scheduled queries.
- 03 Sync high-volume event or tenant data from a Citus cluster into a warehouse for cross-tenant analytics.
- 04 Write CRM or billing records into reference tables so distributed queries can join operational context locally on every node.
Common sync patterns
Serve warehouse results at database speed
Aggregates or model outputs computed in Materialize sync into Citus, where whatever reads from that database gets them without querying the warehouse.
Fresh analytics without loading windows
Because changes stream continuously, analysts query current data instead of waiting for last night's load.
Offload heavy reads
Point analytical queries at the synced copy in Materialize and keep Citus focused on its operational workload.
What you can sync between Citus 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.
| Citus objects | Materialize objects | How this pairing syncs | |
|---|---|---|---|
| Local tables Coordinator-only tables that behave exactly like standard PostgreSQL tables. | Indexes In-memory arrangements that make view reads fast for serving workloads. | Local tables is specific to Citus and Indexes to Materialize — each maps to any object or custom field on the other side. | |
| Schemas Standard Postgres namespaces used to scope what a sync user can read and write. | Clusters Compute pools that isolate ingestion, view maintenance, and serving. | Schemas is specific to Citus and Clusters to Materialize — each maps to any object or custom field on the other side. | |
| Views Curated projections over distributed data, often used as read-only sync sources. | Connections & Secrets Stored credentials and endpoints used by sources and sinks. | Views is specific to Citus and Connections & Secrets to Materialize — each maps to any object or custom field on the other side. | |
| Sequences Key generators that matter when external writes must not collide with application inserts. | Schemas & Databases Namespaces that organize objects a sync targets. | Sequences is specific to Citus and Schemas & Databases to Materialize — each maps to any object or custom field on the other side. | |
| Distributed tables Tables sharded across worker nodes by a distribution column; the main sync target for large datasets. | Tables User-managed tables that accept INSERT/UPDATE/DELETE from sync pipelines. | Distributed tables is specific to Citus and Tables to Materialize — each maps to any object or custom field on the other side. | |
| Reference tables Small lookup tables replicated to every node, synced like ordinary Postgres tables. | Sources Ingestion points (Kafka, Postgres CDC, MySQL CDC, webhook) that feed external data into Materialize. | Reference tables is specific to Citus and Sources to Materialize — each maps to any object or custom field on the other side. |
How changes propagate between Citus 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.
Citus Materialize Sub-second propagation
DetectionChanges in Citus are captured at the source via change data capture — no polling loop against its API. PostgreSQL logical decoding / CDC, with caveats: changes to distributed tables occur on worker shards, so CDC setup differs from single-node Postgres.
DeliveryEach detected change is applied to Materialize as a row-level write, with types converted between the two schemas.
Materialize Citus 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 Citus as a row-level write, with types converted between the two schemas.
What ships with Citus ⇄ Materialize
Connect Citus and Materialize for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Citus–Materialize connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Citus 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 Citus or Materialize record.
Observability
Monitoring
Track your Citus ⇄ Materialize sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Citus and Materialize.
How the Citus and Materialize connectors work
Citus
- Integration surface
- PostgreSQL wire protocol; any standard Postgres driver connects to the coordinator node
- Authentication
- Database credentials (standard PostgreSQL authentication; managed deployments add cloud IAM options)
- Change detection
- PostgreSQL logical decoding / CDC, with caveats: changes to distributed tables occur on worker shards, so CDC setup differs from single-node Postgres
- Capabilities
- read · write · CDC
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 Citus 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.
- 01
Connect your apps
Authenticate Citus 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.
Citus
connected
Materialize
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Citus 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.
objects · Citus ⇄ MaterializeCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Citus MaterializeCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Citus and Materialize integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Citus and Materialize: authenticate both systems, choose the objects to sync (such as Citus's Local tables and Schemas), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Citus: PostgreSQL wire protocol; any standard Postgres driver connects to the coordinator node. Authentication: Database credentials (standard PostgreSQL authentication; managed deployments add cloud IAM options). Materialize: PostgreSQL wire protocol (SQL). Authentication: Database credentials (username/password; app passwords in the managed cloud service). Stacksync manages authentication, retries, and rate limits on both sides.
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Materialize: SUBSCRIBE turns any view into a change stream, giving integrations a native CDC-style read path. Citus: The managed cloud offering is Azure Cosmos DB for PostgreSQL, which is Citus under a Microsoft brand. Stacksync's field mapping accounts for these differences between Citus and Materialize without custom code.
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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 Citus and Materialize records are not retained after a sync operation.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed Citus and Materialize connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Citus–Materialize integration in-house.
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Yes — Stacksync ships production-grade connectors for both Citus and Materialize. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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.
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:
Related integrations
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