Real-time
Two-way sync
Changes in Databricks or Manhattan Associates WMS instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ ERP
Databricks to Manhattan Associates WMS integration — real-time, two-way sync
Keep Databricks and Manhattan Associates WMS 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 Databricks and Manhattan Associates WMS
Put Manhattan Associates WMS's records in Databricks as live tables for reporting and analysis, without extract jobs, and write results back where Manhattan Associates WMS 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 Manhattan Associates WMS carries financials, operations, workforce data, or all three, the analysis belongs in Databricks next to everything else the company measures.
Stacksync syncs Inventory, Items, Shipments & LPNs, Receipts from Manhattan Associates WMS into tables in Databricks continuously, managing API limits and schema drift along the way. The connection is bi-directional, so values computed in Databricks can be written back to fields in Manhattan Associates WMS where that is useful.
Common use cases
- 01 Serve ML feature outputs computed in Databricks to production apps through a synced operational store.
- 02 Land CRM and ERP records in Delta tables continuously so lakehouse models work from current operational data.
- 03 Reconcile ASNs and receipts with procurement systems to close POs automatically.
- 04 Feed labor and throughput data into analytics tools for DC performance reporting.
Common sync patterns
Group reporting across systems
Combine Manhattan Associates WMS's records with data synced from other systems in Databricks for consolidated views no single system can produce.
Write-back where Manhattan Associates WMS exposes writable fields
Classifications or reference values computed in Databricks sync back onto the corresponding records in Manhattan Associates WMS.
Where Manhattan Associates WMS holds the books: finance reporting from live data
Financial records land in Databricks as they change, so period-end reporting queries current numbers rather than last night's extract.
What you can sync between Databricks and Manhattan Associates WMS
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.
| Databricks objects | Manhattan Associates WMS objects | How this pairing syncs | |
|---|---|---|---|
| Change Data Feed Row-level change records on Delta tables that drive incremental reads. | Inventory On-hand, allocated, and available positions read out across the DC network. | Change Data Feed is specific to Databricks and Inventory to Manhattan Associates WMS — each maps to any object or custom field on the other side. | |
| Catalogs Top level of the Unity Catalog namespace, scoping which schemas a sync can address. | Items Item master and packaging data kept consistent with the ERP catalog. | Catalogs is specific to Databricks and Items to Manhattan Associates WMS — each maps to any object or custom field on the other side. | |
| Schemas Group tables and views; syncs typically target a dedicated schema per source system. | Shipments & LPNs Ship confirmations, cartons, and tracking pushed back to order sources. | Schemas is specific to Databricks and Shipments & LPNs to Manhattan Associates WMS — each maps to any object or custom field on the other side. | |
| Delta Tables The primary read and write target; operational data lands here as managed or external tables. | Receipts Receiving transactions reconciled against POs in the ERP. | Delta Tables is specific to Databricks and Receipts to Manhattan Associates WMS — each maps to any object or custom field on the other side. | |
| Views Curated read-only projections used as sync sources for downstream tools. | Locations & Zones Facility topology referenced when interpreting inventory positions. | Views is specific to Databricks and Locations & Zones to Manhattan Associates WMS — each maps to any object or custom field on the other side. | |
| Materialized Views Precomputed results read on a schedule for reverse-ETL style syncs. | Returns Return receipts synced so upstream systems reflect disposition and restock. | Materialized Views is specific to Databricks and Returns to Manhattan Associates WMS — each maps to any object or custom field on the other side. |
How changes propagate between Databricks and Manhattan Associates WMS
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.
Databricks Manhattan Associates WMS Sub-second propagation
DetectionChanges in Databricks are captured at the source via change data capture — no polling loop against its API. Delta Lake Change Data Feed for row-level changes.
DeliveryEach detected change is written to Manhattan Associates WMS through its API, with automatic retries and rate-limit backoff.
Manhattan Associates WMS Databricks Interval-based propagation
DetectionStacksync polls Manhattan Associates WMS for changes on an incremental schedule, reading only records changed since the previous pass. Polling on modified timestamps.
DeliveryEach detected change is applied to Databricks as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- Databricks: Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits.
What ships with Databricks ⇄ Manhattan Associates WMS
Connect Databricks and Manhattan Associates WMS for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Databricks–Manhattan Associates WMS connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Databricks or Manhattan Associates WMS 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 Databricks or Manhattan Associates WMS record.
Observability
Monitoring
Track your Databricks ⇄ Manhattan Associates WMS sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Databricks and Manhattan Associates WMS.
How the Databricks and Manhattan Associates WMS connectors work
Databricks
- Integration surface
- SQL over JDBC/ODBC via SQL warehouses, plus a REST API including statement execution
- Authentication
- Personal access tokens or OAuth machine-to-machine credentials for service principals
- Change detection
- Delta Lake Change Data Feed for row-level changes; otherwise incremental polling on watermark columns
- Capabilities
- read · write · CDC
- Rate limits
- Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits
Manhattan Associates WMS
- Integration surface
- REST API on Manhattan Active WM; database tables and message-based interfaces on legacy on-premises versions
- Authentication
- OAuth 2.0 on Manhattan Active; database credentials on legacy deployments
- Change detection
- Polling on modified timestamps; Manhattan Active also supports event/message-driven integration patterns
- Capabilities
- read · write
How it works
How to connect Databricks to Manhattan Associates WMS — 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 Databricks and Manhattan Associates WMS with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Databricks
connected
Manhattan Associates WMS
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Databricks and Manhattan Associates WMS 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 · Databricks ⇄ Manhattan Associates WMSCustomers 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.
Databricks Manhattan Associates WMSCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Databricks and Manhattan Associates WMS integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Databricks and Manhattan Associates WMS: authenticate both systems, choose the objects to sync (such as Databricks's Change Data Feed and Catalogs), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Yes — Stacksync ships production-grade connectors for both Databricks and Manhattan Associates WMS. 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 Databricks: Delta Lake Change Data Feed for row-level changes; otherwise incremental polling on watermark columns. On Manhattan Associates WMS: Polling on modified timestamps; Manhattan Active also supports event/message-driven integration patterns. 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 Databricks side: SQL Warehouses, Change Data Feed, Catalogs, Schemas, plus custom fields where Databricks exposes them. On the Manhattan Associates WMS side: Inventory, Items, Shipments & LPNs, Receipts. 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.
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Common patterns for Databricks and Manhattan Associates WMS: Group reporting across systems; Write-back where Manhattan Associates WMS exposes writable fields; Where Manhattan Associates WMS holds the books: finance reporting from live data. Combine Manhattan Associates WMS's records with data synced from other systems in Databricks for consolidated views no single system can produce.
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.
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GDPR
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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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No integrations match .
