Real-time
Two-way sync
Changes in Infor M3 or Snowflake instantly reflect in both systems. No stale data, no manual imports.
ERP ⇄ Data warehouse
Infor M3 to Snowflake integration — real-time, two-way sync
Keep Infor M3 and Snowflake 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
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Migrated from Mulesoft
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Migrated from Matillion
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Migrated from Fivetran
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Migrated from Celigo
Why teams connect Infor M3 and Snowflake
Put Infor M3's records in Snowflake as live tables for reporting and analysis, without extract jobs, and write results back where Infor M3 can use them.
ERP data is some of the most asked-for data in the warehouse and some of the hardest to get: the record types are many, the APIs are strict, and extract jobs are brittle. Whether Infor M3 carries financials, operations, workforce data, or all three, the analysis belongs in Snowflake next to everything else the company measures.
Stacksync syncs Items, Customers, Suppliers, Customer Orders from Infor M3 into tables in Snowflake continuously, managing API limits and schema drift along the way. The connection is bi-directional, so values computed in Snowflake can be written back to fields in Infor M3 where that is useful.
Common use cases
- Push product usage aggregates from Snowflake into sales and success tools for account prioritization
- Feed finance reconciliation models from ERP data landed in Snowflake on a continuous basis
- Consolidate M3 transactional data into an analytics database for cross-plant reporting
- Sync M3 item master and inventory balances to commerce or CPQ systems so quotes price against live stock
Where Infor M3 holds the books: finance reporting from live data
Financial records land in Snowflake as they change, so period-end reporting queries current numbers rather than last night's extract.
Where Infor M3 is the HR system of record: workforce analytics
Worker and organization data syncs into Snowflake for headcount, cost, and planning analysis alongside other company data.
Where Infor M3 runs operations: order and supply analysis
Operational records become queryable tables in Snowflake, joinable with sales and finance data.
What you can sync between Infor M3 and Snowflake
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.
| Infor M3 objects | Snowflake objects | |
|---|---|---|
| Items Item master records provide the SKU, unit, and attribute data other systems price and sell against. | Databases Top-level containers that scope which data a sync can touch. | |
| Customers Customer master records sync with CRM account records to keep one shared customer file. | Schemas Namespaces within a database used to organize synced tables. | |
| Suppliers Supplier records align procurement tools with the vendors M3 purchases from. | Tables The main landing and activation target for synced records. | |
| Customer Orders Orders created in commerce or CRM systems land in M3 for fulfillment and invoicing. | Views Modeled projections used as the source side of outbound syncs. | |
| Purchase Orders PO headers and lines sync outward so buyers and receiving teams see the same demand. | Materialized Views Precomputed results synced outward for low-latency reads. | |
| Manufacturing Orders Production order status feeds portals and CRMs so promised dates reflect the shop floor. | Streams Row-level change records on a table, consumed to process deltas instead of full scans. |
What ships with Infor M3 ⇄ Snowflake
Connect Infor M3 and Snowflake for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Infor M3–Snowflake connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Infor M3 or Snowflake 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 Infor M3 or Snowflake record.
Observability
Monitoring
Track your Infor M3 ⇄ Snowflake sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Infor M3 and Snowflake.
How the Infor M3 and Snowflake connectors work
Infor M3
- Integration surface
- REST API (M3 API programs exposed through the Infor ION API gateway)
- Authentication
- OAuth 2.0 via Infor OS / ION API authorization
- Change detection
- Event publishing through Infor ION (Business Object Documents), configured in ION, or scheduled polling of API endpoints
- Capabilities
- read · write · webhooks
- Rate limits
- Subject to Infor ION API gateway throttling policies
Snowflake
- Integration surface
- SQL via JDBC/ODBC and native drivers, plus the Snowflake SQL REST API
- Authentication
- Dedicated Snowflake service user + role with RSA key-pair authentication (Stacksync-provided public key), created via a setup script requiring SECURITY_ADMIN and ACCOUNTADMIN roles
- Change detection
- Not explicitly stated; the setup script grants "create stream" on synced schemas (Snowflake streams), but the docs do not name the change-capture mechanism
- Capabilities
- read · write · CDC
- Rate limits
- No conventional API rate limits; cost and throughput are governed by virtual warehouse size and running time
How it works
How to connect Infor M3 to Snowflake — 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 Infor M3 and Snowflake with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Infor M3
connected
Snowflake
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Infor M3 and Snowflake 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 · Infor M3 ⇄ SnowflakeCustomers 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.
Infor M3 SnowflakeCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Infor M3 and Snowflake integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Infor M3 and Snowflake: authenticate both systems, choose the objects to sync (such as Infor M3's Items and Customers), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed Infor M3 and Snowflake connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Infor M3–Snowflake integration in-house.
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Yes — Stacksync ships production-grade connectors for both Infor M3 and Snowflake. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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Change detection on Infor M3: Event publishing through Infor ION (Business Object Documents), configured in ION, or scheduled polling of API endpoints. On Snowflake: Not explicitly stated; the setup script grants "create stream" on synced schemas (Snowflake streams), but the docs do not name the change-capture mechanism. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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On the Snowflake side: Tasks, VARIANT Columns, Virtual Warehouses, Databases, plus custom fields where Snowflake exposes them. On the Infor M3 side: Items, Customers, Suppliers, Customer Orders. Stacksync auto-detects both schemas and converts types between the two systems.
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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.
SECURITY
Security teams love 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
CSA STAR
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
Every pair below is a real-time, two-way sync. Search all 386 integrations available for Infor M3 and Snowflake.
Popular · 8 of 386
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Infor M3 ⇄ Google Cloud Platform -
Infor M3 ⇄ Greenplum -
Infor M3 ⇄ IBM Netezza -
Infor M3 ⇄ Materialize -
Snowflake ⇄ Odoo -
Snowflake ⇄ Blue Yonder WMS -
Snowflake ⇄ Brightpearl -
Snowflake ⇄ Cetec ERP
No integrations match .
