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Data warehouse ⇄ E-commerce

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

Keep Databricks and Magento 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 Magento

Make Databricks the analytics and enrichment layer behind Magento: orders, products, and customers stay current in both directions.

Databricks is the analytical store where the business joins, models, and reports on its data; Magento runs the storefront, catalog, and transactions that generate most of it. The overlap is every record that has to be counted and enriched on one side and acted on the other — and when the bridge is a nightly export, the warehouse reports on yesterday while the store operates without the segments and metrics the warehouse just computed.

Stacksync syncs Volumes, SQL Warehouses, Change Data Feed, Catalogs in Databricks with Orders, Customers, Inventory source items (MSI), Invoices in Magento field by field, in real time, and in both directions. Transactional records land in the warehouse as they change, computed attributes and cleaned catalog data flow back to the store, and you decide which system owns which fields so Stacksync resolves conflicts by rules you set.

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 Master Products, prices, and Category assignments in an ERP or PIM and write them into Magento's catalog by SKU.
  • 04 Keep MSI inventory source-item quantities aligned between a WMS/ERP and Magento so storefront stock matches the warehouse.

Common sync patterns

Where Magento accepts writes: push computed attributes back

Segments, lifetime value, and scores built in Databricks write onto the matching records in Magento, so merchandising and messaging act on warehouse logic.

One product catalog

Where both systems hold product or catalog data, cleaned and enriched attributes stay aligned so the store and the warehouse describe the same items.

Inventory and order status reconciled

Stock levels and order or fulfillment status move between Databricks and Magento so counts and states agree across reporting and operations.

What you can sync between Databricks and Magento

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 Magento objects How this pairing syncs
SQL Warehouses The compute endpoint a sync connects to for query execution. Carts / quotes Active and guest carts (quotes) with items and totals; read for abandoned-cart analysis (not available on the Cloud Service subset). SQL Warehouses is specific to Databricks and Carts / quotes to Magento — 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. Products Catalog items keyed by SKU; carry created_at/updated_at for incremental polling and are written two-way from a PIM or ERP into the storefront. Change Data Feed is specific to Databricks and Products to Magento — 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. Configurable / variant products Parent configurable products link to simple product variants by attribute; synced so size/color SKUs and their prices stay aligned with source systems. Catalogs is specific to Databricks and Configurable / variant products to Magento — 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. Categories Catalog tree and product-to-category assignments; written into Magento to control merchandising and read out for taxonomy reporting. Schemas is specific to Databricks and Categories to Magento — 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. Orders Sales orders with line items, totals, and status; typically read out of Magento into a warehouse or ERP for fulfillment and revenue reporting. Delta Tables is specific to Databricks and Orders to Magento — each maps to any object or custom field on the other side.
Views Curated read-only projections used as sync sources for downstream tools. Customers Customer accounts and address book; synced two-way with a CRM so order history and contact records stay consistent. Views is specific to Databricks and Customers to Magento — each maps to any object or custom field on the other side.

How changes propagate between Databricks and Magento

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

Magento Databricks Sub-second propagation

DetectionMagento notifies Stacksync of record changes through webhook events. Polling with searchCriteria filters on updated_at (catalog, sales, and customer entities carry created_at/updated_at).

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.
  • Magento: No fixed request-per-minute cap on PaaS/on-prem; responses page via searchCriteria pageSize/currentPage under a default maximum page size of 300 (Web API Input Limits), with /async/bulk endpoints for large writes.
What ships with Databricks ⇄ Magento

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Databricks or Magento 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 Magento record.

Observability

Monitoring

Track your Databricks ⇄ Magento 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 Magento.

How the Databricks and Magento 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

Magento

Integration surface
REST and GraphQL Web APIs (SOAP also available)
Authentication
Token-based OAuth: an integration's access token (consumer key/secret + access token/secret) or a Bearer admin token (default 4-hour expiry); Adobe Commerce as a Cloud Service authenticates via Adobe IMS (OAuth 2)
Change detection
Polling with searchCriteria filters on updated_at (catalog, sales, and customer entities carry created_at/updated_at); optional near-real-time via the Adobe Commerce Webhooks / Adobe I/O Events modules (order/created, product/updated, customer/created)
Capabilities
read · write · webhooks
Rate limits
No fixed request-per-minute cap on PaaS/on-prem; responses page via searchCriteria pageSize/currentPage under a default maximum page size of 300 (Web API Input Limits), with /async/bulk endpoints for large writes.
How it works

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

    Choose tables

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

Databricks and Magento 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.

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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 508 integrations available for Databricks and Magento.

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