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Data warehouse ⇄ Database

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

Keep Materialize and MongoDB in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

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

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Why teams connect Materialize and MongoDB

Connect MongoDB 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 MongoDB'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 MongoDB where the services that read from it get them at normal query latency.

Stacksync covers both directions with one connection. Tables or collections in MongoDB sync into Materialize in real time, and result tables in Materialize sync back into MongoDB, with schema and type mapping between the two systems handled for you.

Common use cases

  • 01 Sync operational CRM or ERP data into Materialize so real-time views stay current without batch loads.
  • 02 Read computed view results back into a CRM or application database as derived fields.
  • 03 Capture change stream events and propagate them to SaaS tools in near real time instead of running batch exports.
  • 04 Keep a MongoDB-backed product catalog aligned with an ERP's item master in both directions.

Common sync patterns

Operational data in the warehouse, minus the pipeline

Rows from MongoDB land in Materialize as they change, replacing hand-built CDC and batch extract jobs.

Serve warehouse results at database speed

Aggregates or model outputs computed in Materialize sync into MongoDB, 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.

What you can sync between Materialize and MongoDB

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.

Materialize objects MongoDB objects How this pairing syncs
Indexes In-memory arrangements that make view reads fast for serving workloads. Indexes Keep lookups by sync key fast on large collections. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Schemas & Databases Namespaces that organize objects a sync targets. Embedded documents and arrays Nested structures that syncs flatten or map to related records in relational targets. Schemas & Databases is specific to Materialize and Embedded documents and arrays to MongoDB — each maps to any object or custom field on the other side.
Tables User-managed tables that accept INSERT/UPDATE/DELETE from sync pipelines. Views Read-only aggregation-defined sources for filtered sync datasets. Tables is specific to Materialize and Views to MongoDB — each maps to any object or custom field on the other side.
Sources Ingestion points (Kafka, Postgres CDC, MySQL CDC, webhook) that feed external data into Materialize. Change streams The oplog-backed event feed that powers real-time change capture. Sources is specific to Materialize and Change streams to MongoDB — each maps to any object or custom field on the other side.
Materialized Views Incrementally maintained query results that syncs read as continuously up-to-date datasets. GridFS files Chunked file storage whose metadata can be referenced by synced documents. Materialized Views is specific to Materialize and GridFS files to MongoDB — each maps to any object or custom field on the other side.
Sinks Outbound connections that emit view changes to Kafka topics. Databases Logical groupings of collections that scope a sync connection. Sinks is specific to Materialize and Databases to MongoDB — each maps to any object or custom field on the other side.

How changes propagate between Materialize and MongoDB

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.

Materialize MongoDB 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 MongoDB as a row-level write, with types converted between the two schemas.

MongoDB Materialize Sub-second propagation

DetectionChanges in MongoDB are captured at the source via change data capture — no polling loop against its API. MongoDB oplog and change streams (requires the database to run as a replica set — even single-node).

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

What ships with Materialize ⇄ MongoDB

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

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

Observability

Monitoring

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

Trading partners

EDI

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

How the Materialize and MongoDB connectors work

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

MongoDB

Integration surface
MongoDB wire protocol via official drivers; Atlas additionally offers an administration REST API for cluster management
Authentication
Database credentials (username/password) or TLS/SSL X.509 certificate (.pem upload), entered individually or via a MongoDB connection string (SRV or standard); Stacksync IP allowlisting required
Change detection
MongoDB oplog and change streams (requires the database to run as a replica set — even single-node); Stacksync leverages these built-in tools to track changes in real time
Capabilities
read · write · CDC
MongoDB setup guide
How it works

How to connect Materialize to MongoDB — 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 Materialize and MongoDB 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
    Materialize connected
    MongoDB connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Materialize and MongoDB 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 · Materialize ⇄ MongoDB
    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
    Materialize MongoDB
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Materialize and MongoDB 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 471 integrations available for Materialize and MongoDB.

Popular · 5 of 471
All Materialize integrations All MongoDB integrations Browse all integrations
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