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Data warehouse ⇄ ERP

Databricks to Linnworks integration — real-time, two-way sync

Keep Databricks and Linnworks 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 Databricks and Linnworks

Put Linnworks's records in Databricks as live tables for reporting and analysis, without extract jobs, and write results back where Linnworks 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 Linnworks carries financials, operations, workforce data, or all three, the analysis belongs in Databricks next to everything else the company measures.

Stacksync syncs Locations, Purchase Orders, Suppliers, Channel Listings from Linnworks 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 Linnworks where that is useful.

Common use cases

  • 01 Use Change Data Feed to propagate only changed rows to downstream apps instead of full-table scans.
  • 02 Serve ML feature outputs computed in Databricks to production apps through a synced operational store.
  • 03 Sync product and listing data with a PIM so channel listings stay aligned with the catalog
  • 04 Push customer and order data to a CRM or marketing platform for post-purchase campaigns

Common sync patterns

Where Linnworks runs operations: order and supply analysis

Operational records become queryable tables in Databricks, joinable with sales and finance data.

Group reporting across systems

Combine Linnworks's records with data synced from other systems in Databricks for consolidated views no single system can produce.

Write-back where Linnworks exposes writable fields

Classifications or reference values computed in Databricks sync back onto the corresponding records in Linnworks.

What you can sync between Databricks and Linnworks

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 Linnworks objects How this pairing syncs
Volumes Unity Catalog file storage used for staging bulk loads. Suppliers Vendor records keep procurement data consistent across tools. Volumes is specific to Databricks and Suppliers to Linnworks — each maps to any object or custom field on the other side.
SQL Warehouses The compute endpoint a sync connects to for query execution. Channel Listings Marketplace and webstore listing mappings tie channel products to internal SKUs. SQL Warehouses is specific to Databricks and Channel Listings to Linnworks — each maps to any object or custom field on the other side.
Change Data Feed Row-level change records on Delta tables that drive incremental reads. Returns & Refunds Post-sale records flow to finance and support systems. Change Data Feed is specific to Databricks and Returns & Refunds to Linnworks — 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. Shipping Services Carrier and service definitions support label and tracking data in order syncs. Catalogs is specific to Databricks and Shipping Services to Linnworks — 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. Open Orders Unshipped orders aggregated from sales channels sync into ERPs and fulfillment systems. Schemas is specific to Databricks and Open Orders to Linnworks — 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. Processed Orders Completed orders feed accounting and warehouse-based margin reporting. Delta Tables is specific to Databricks and Processed Orders to Linnworks — each maps to any object or custom field on the other side.

How changes propagate between Databricks and Linnworks

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 Linnworks 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 Linnworks through its API, with automatic retries and rate-limit backoff.

Linnworks Databricks Interval-based propagation

DetectionStacksync polls Linnworks for changes on an incremental schedule, reading only records changed since the previous pass. Polling on order and stock endpoints.

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.
  • Linnworks: Per-endpoint rate limits apply on the Linnworks API.
What ships with Databricks ⇄ Linnworks

Connect Databricks and Linnworks for flexible, real-time data sync.

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

Real-time

Two-way sync

Changes in Databricks or Linnworks instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Databricks or Linnworks 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 Linnworks record.

Observability

Monitoring

Track your Databricks ⇄ Linnworks 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 Linnworks.

How the Databricks and Linnworks 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

Linnworks

Integration surface
REST API
Authentication
Application credentials and an install token exchanged for a session token
Change detection
Polling on order and stock endpoints
Capabilities
read · write
Rate limits
Per-endpoint rate limits apply on the Linnworks API
How it works

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

    Choose tables

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

Databricks and Linnworks 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
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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:

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 548 integrations available for Databricks and Linnworks.

Popular · 6 of 548
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