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Data warehouse ⇄ E-commerce

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

Keep Databricks and Shopware 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 Shopware

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

Databricks is the analytical store where the business joins, models, and reports on its data; Shopware 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 Views, Materialized Views, Volumes, SQL Warehouses in Databricks with Orders, Order Line Items, Order Deliveries, Order Transactions in Shopware 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 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 Two-way sync of the `product` catalog — titles, nested price arrays, and stock — between Shopware and an ERP or PIM so pricing and inventory stay aligned.
  • 04 Stream new `order` records with their `order_line_item`, `order_delivery`, and `order_transaction` rows into a warehouse or accounting system for revenue and fulfillment reporting.

Common sync patterns

Live analytics on store activity

Orders, products, and customer records from Shopware land in Databricks as they change, so dashboards and models read current data instead of last night's export.

Where Shopware accepts writes: push computed attributes back

Segments, lifetime value, and scores built in Databricks write onto the matching records in Shopware, 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.

What you can sync between Databricks and Shopware

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 Shopware objects How this pairing syncs
Change Data Feed Row-level change records on Delta tables that drive incremental reads. Orders Order headers (`order`) with totals, state, and sales-channel reference; read out to accounting and written back for status updates. Change Data Feed is specific to Databricks and Orders to Shopware — 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. Order Line Items Per-order product rows (`order_line_item`); read alongside the order for revenue and fulfillment reporting. Catalogs is specific to Databricks and Order Line Items to Shopware — 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. Order Deliveries Shipping records (`order_delivery`) carrying delivery state and tracking codes; written back from a 3PL or WMS. Schemas is specific to Databricks and Order Deliveries to Shopware — 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. Order Transactions Payment records (`order_transaction`) holding payment method and state; read to reconcile against a billing or finance system. Delta Tables is specific to Databricks and Order Transactions to Shopware — each maps to any object or custom field on the other side.
Views Curated read-only projections used as sync sources for downstream tools. Sales Channels Per-storefront configuration (`sales_channel`); used to scope and consolidate orders and customers across multiple storefronts. Views is specific to Databricks and Sales Channels to Shopware — 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. Media Media assets (`media`) such as product images; referenced by id so file URLs and metadata sync into downstream catalogs. Materialized Views is specific to Databricks and Media to Shopware — each maps to any object or custom field on the other side.

How changes propagate between Databricks and Shopware

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

Shopware Databricks Sub-second propagation

DetectionShopware notifies Stacksync of record changes through webhook events. App-system webhooks on entity events (product.written, order.written, customer.written) deliver the changed record's primaryKey and updated field.

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.
  • Shopware: No general throttle on Admin API entity endpoints; Shopware's RateLimiter guards only specific routes (login, oauth, password reset, guest order/contact) and is configurable on self-hosted stores.
What ships with Databricks ⇄ Shopware

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Databricks or Shopware 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 Shopware record.

Observability

Monitoring

Track your Databricks ⇄ Shopware 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 Shopware.

How the Databricks and Shopware 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

Shopware

Integration surface
Admin API (REST / JSON:API) with a bulk POST /api/_action/sync endpoint
Authentication
OAuth 2.0 — client-credentials grant using an Integration's Access Key ID + Secret Access Key, or resource-owner password grant for a user; access tokens expire after 10 minutes
Change detection
App-system webhooks on entity events (product.written, order.written, customer.written) deliver the changed record's primaryKey and updated field names; otherwise poll on the updatedAt / createdAt fields
Capabilities
read · write · webhooks
Rate limits
No general throttle on Admin API entity endpoints; Shopware's RateLimiter guards only specific routes (login, oauth, password reset, guest order/contact) and is configurable on self-hosted stores
How it works

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

    Choose tables

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

Databricks and Shopware 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 Shopware.

Popular · 8 of 508
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