Two-way sync
Changes in Apache Cassandra or Infor M3 instantly reflect in both systems. No stale data, no manual imports.
Keep Apache Cassandra 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.
ERP data sits behind interfaces built for the ERP's own modules, not for your internal systems. Teams that need those records, for reporting services, internal tools, or automations, end up writing integration code against a strict API and maintaining it through every upgrade.
Stacksync mirrors Manufacturing Orders, Inventory Balances, Invoices, Warehouses from Infor M3 into Apache Cassandra and keeps both sides consistent in real time. Whatever Infor M3 is the system of record for, whether financials, operations, people, or procurement, those records become rows your code can query, and changes written in Apache Cassandra sync back into Infor M3 with its validations respected.
Updates in Infor M3 arrive as row changes in Apache Cassandra, so jobs and triggers can respond as the business record changes.
Worker and org records stay current in Apache Cassandra for provisioning, access, and reporting systems that read from the database.
Choose exactly which tables and fields may flow from Apache Cassandra back into Infor M3, keeping the ERP authoritative.
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 Cassandra objects | Infor M3 objects | |
|---|---|---|
| Tables Wide-column tables addressed by partition key, the unit of row-level sync. | Inventory Balances On-hand quantities by warehouse drive available-to-promise in downstream channels. | |
| Partitions and Rows Records located by partition and clustering keys during reads and upserts. | Invoices Billing documents flow to finance and CRM tools for AR visibility. | |
| Materialized Views Server-maintained denormalized views; considered experimental and disabled by default in recent releases. | Warehouses Warehouse and facility records scope inventory and order data during mapping. | |
| Secondary Indexes Optional indexes that allow filtered reads outside the partition key. | Price Lists Pricing data keeps quoting tools consistent with the prices M3 will actually invoice. | |
| User-Defined Types Composite column types that syncs must flatten or map to structured fields. | Items Item master records provide the SKU, unit, and attribute data other systems price and sell against. | |
| Collections List, set, and map columns handled with type-aware field mapping. | Customers Customer master records sync with CRM account records to keep one shared customer file. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Cassandra–Infor M3 connection.
Changes in Apache Cassandra or Infor M3 instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Apache Cassandra or Infor M3 data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Apache Cassandra or Infor M3 record.
Track your Apache Cassandra ⇄ Infor M3 sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Apache Cassandra and Infor M3.
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.
Authenticate Apache Cassandra 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.
Pick the Apache Cassandra 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.
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Yes. Stacksync provides a managed, real-time two-way integration between Apache Cassandra and Infor M3: authenticate both systems, choose the objects to sync (such as Apache Cassandra's Tables and Partitions and Rows), map fields visually, and changes propagate both ways in milliseconds — no code required.
On the Apache Cassandra side: Secondary Indexes, User-Defined Types, Collections, Counters, plus custom fields where Apache Cassandra exposes them. On the Infor M3 side: Manufacturing Orders, Inventory Balances, Invoices, Warehouses. Stacksync auto-detects both schemas and converts types between the two systems.
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.
Common patterns for Apache Cassandra and Infor M3: React to ERP changes; Where Infor M3 is the HR system of record: people data for internal systems; Controlled write-back. Updates in Infor M3 arrive as row changes in Apache Cassandra, so jobs and triggers can respond as the business record changes.
Apache Cassandra: CQL over the Cassandra native binary protocol. Authentication: Database credentials (password authenticator); TLS and role-based grants where configured. Infor M3: REST API (M3 API programs exposed through the Infor ION API gateway). Authentication: OAuth 2.0 via Infor OS / ION API authorization. Stacksync manages authentication, retries, and rate limits on both sides.
Apache Cassandra: Data modeling is query-first and denormalized: tables are designed around partition keys, and there are no joins, so syncs address rows by partition and clustering keys. Infor M3: M3 business logic is exposed through M3 API programs (MI programs), which Infor publishes as REST endpoints through the ION API gateway rather than as a single flat resource model. Stacksync's field mapping accounts for these differences between Apache Cassandra and Infor M3 without custom code.
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.
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Securely connects to your systems with:
Every pair below is a real-time, two-way sync. Search all 386 integrations available for Apache Cassandra and Infor M3.