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Data warehouse ⇄ ERP

Apache Hive to Infor M3 integration — real-time, two-way sync

Keep Apache Hive and Infor M3 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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Why teams connect Apache Hive and Infor M3

Put Infor M3's records in Apache Hive 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 Apache Hive next to everything else the company measures.

Stacksync syncs Customers, Suppliers, Customer Orders, Purchase Orders from Infor M3 into tables in Apache Hive continuously, managing API limits and schema drift along the way. The connection is bi-directional, so values computed in Apache Hive can be written back to fields in Infor M3 where that is useful.

Common use cases

  • Bridge a legacy Hadoop warehouse to a cloud warehouse during migration by syncing tables continuously.
  • Extract curated Hive tables into operational databases or SaaS tools so business teams use data locked in Hadoop.
  • Keep supplier and purchase order data aligned between M3 and procurement tools
  • Consolidate M3 transactional data into an analytics database for cross-plant reporting

Where Infor M3 holds the books: finance reporting from live data

Financial records land in Apache Hive 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 Apache Hive 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 Apache Hive, joinable with sales and finance data.

What you can sync between Apache Hive and Infor M3

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.

Apache Hive objects Infor M3 objects
Managed Tables Tables whose data lifecycle Hive controls, used as warehouse destinations. Warehouses Warehouse and facility records scope inventory and order data during mapping.
External Tables Tables over existing files in HDFS or object storage, read without moving data. Price Lists Pricing data keeps quoting tools consistent with the prices M3 will actually invoice.
Partitions Directory-mapped subsets (often by date) that bound incremental sync reads. Items Item master records provide the SKU, unit, and attribute data other systems price and sell against.
Views Logical views readable as modeled sources. Customers Customer master records sync with CRM account records to keep one shared customer file.
Materialized Views Precomputed results available in newer Hive versions for faster reads. Suppliers Supplier records align procurement tools with the vendors M3 purchases from.
ACID Tables ORC-backed transactional tables that support row-level insert, update, and delete. Customer Orders Orders created in commerce or CRM systems land in M3 for fulfillment and invoicing.
What ships with Apache Hive ⇄ Infor M3

Connect Apache Hive and Infor M3 for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Hive–Infor M3 connection.

Real-time

Two-way sync

Changes in Apache Hive or Infor M3 instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Hive or Infor M3 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 Apache Hive or Infor M3 record.

Observability

Monitoring

Track your Apache Hive ⇄ Infor M3 sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Apache Hive and Infor M3.

How the Apache Hive and Infor M3 connectors work

Apache Hive

Integration surface
SQL (HiveQL) over JDBC/ODBC via HiveServer2 (Thrift)
Authentication
Deployment-dependent: Kerberos, LDAP, or username/password
Change detection
Polling on partition values or timestamp columns; no general-purpose change log for external consumers
Capabilities
read · write
Rate limits
No API quotas; query latency reflects the batch-oriented execution engine underneath

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
How it works

How to connect Apache Hive to Infor M3 — 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 Apache Hive and Infor M3 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
    Apache Hive connected
    Infor M3 connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Apache Hive and Infor M3 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 · Apache Hive ⇄ Infor M3
    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
    Apache Hive Infor M3
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Apache Hive and Infor M3 integration FAQ

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.

Learn more about security
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:

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 386 integrations available for Apache Hive and Infor M3.

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