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E-commerce ⇄ Data warehouse

Bigcommerce to Cloudera Data Platform integration — real-time, two-way sync

Keep Bigcommerce and Cloudera Data Platform 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
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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Bigcommerce and Cloudera Data Platform

Make Cloudera Data Platform the analytics and enrichment layer behind Bigcommerce: orders, products, and customers stay current in both directions.

Cloudera Data Platform is the analytical store where the business joins, models, and reports on its data; Bigcommerce 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 Object store / HDFS files, Databases, Hive tables, Impala tables in Cloudera Data Platform with Brands, Inventory, Price Lists, Shipments in Bigcommerce 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 Consolidate tables from on-prem and cloud CDP environments into a single cloud warehouse target.
  • 02 Sync curated CDP tables into an operational Postgres so applications query a low-latency copy instead of hitting the cluster.
  • 03 Write Inventory levels from a WMS or ERP onto BigCommerce Variants and SKUs so storefront availability reflects warehouse on-hand counts.
  • 04 Sync Customers and customer groups two-way with a CRM so marketing and support see the same accounts and addresses as the storefront.

Common sync patterns

Live analytics on store activity

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

Where Bigcommerce accepts writes: push computed attributes back

Segments, lifetime value, and scores built in Cloudera Data Platform write onto the matching records in Bigcommerce, 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 Bigcommerce and Cloudera Data Platform

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.

Bigcommerce objects Cloudera Data Platform objects How this pairing syncs
Customers V3 customer accounts, customer groups, and addresses; synced two-way with a CRM so storefront and GTM records match. Iceberg tables Open table format tables in newer CDP versions, with snapshot metadata usable for incremental reads. Customers is specific to Bigcommerce and Iceberg tables to Cloudera Data Platform — each maps to any object or custom field on the other side.
Categories Catalog V3 category tree; mapped for merchandising and kept aligned with a product master or PIM. Views SQL views that can present curated, sync-ready projections of raw lake data. Categories is specific to Bigcommerce and Views to Cloudera Data Platform — each maps to any object or custom field on the other side.
Brands Catalog V3 brand records linked to products; kept aligned with a product master or PIM so brand names and pages stay consistent. Partitions Table partitions (often by date) that incremental extraction jobs use to scope reads. Brands is specific to Bigcommerce and Partitions to Cloudera Data Platform — each maps to any object or custom field on the other side.
Inventory Product- or variant-level stock, plus multi-location counts via the V3 Inventory API; written from a WMS to reflect on-hand quantities. Object store / HDFS files Underlying Parquet or ORC files on HDFS or cloud storage backing the tables. Inventory is specific to Bigcommerce and Object store / HDFS files to Cloudera Data Platform — each maps to any object or custom field on the other side.
Price Lists V3 price lists and records driving customer-group and B2B pricing; pushed from an ERP so tiered prices stay current. Databases Logical namespaces in the shared Hive Metastore that group tables for access control and syncs. Price Lists is specific to Bigcommerce and Databases to Cloudera Data Platform — each maps to any object or custom field on the other side.
Shipments Order shipments with tracking numbers; created in BigCommerce from a 3PL or fulfillment system as packages ship. Hive tables Warehouse tables queried over JDBC/ODBC; classic managed tables are append-oriented. Shipments is specific to Bigcommerce and Hive tables to Cloudera Data Platform — each maps to any object or custom field on the other side.

How changes propagate between Bigcommerce and Cloudera Data Platform

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.

Bigcommerce Cloudera Data Platform Sub-second propagation

DetectionBigcommerce notifies Stacksync of record changes through webhook events. Webhooks push near-real-time events (store/order/*, store/product/*, store/customer/* and more).

DeliveryEach detected change is applied to Cloudera Data Platform as a row-level write, with types converted between the two schemas.

Cloudera Data Platform Bigcommerce Interval-based propagation

DetectionStacksync polls Cloudera Data Platform for changes on an incremental schedule, reading only records changed since the previous pass. Polling via SQL on timestamp or partition columns.

DeliveryEach detected change is written to Bigcommerce through its API, with automatic retries and rate-limit backoff.

Rate-limit considerations

  • Bigcommerce: OAuth quota refreshes every 30 seconds and varies by plan (about 20,000 requests/hour on Standard and Plus, 60,000 on Pro, higher on Enterprise); the X-Rate-Limit-Requests-Left header reports remaining calls.
  • Cloudera Data Platform: Constrained by cluster capacity and admission control rather than API rate limits.
What ships with Bigcommerce ⇄ Cloudera Data Platform

Connect Bigcommerce and Cloudera Data Platform for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Bigcommerce–Cloudera Data Platform connection.

Real-time

Two-way sync

Changes in Bigcommerce or Cloudera Data Platform instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Bigcommerce or Cloudera Data Platform 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 Bigcommerce or Cloudera Data Platform record.

Observability

Monitoring

Track your Bigcommerce ⇄ Cloudera Data Platform sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Bigcommerce and Cloudera Data Platform.

How the Bigcommerce and Cloudera Data Platform connectors work

Bigcommerce

Integration surface
REST Management API (V2 and V3), plus GraphQL Storefront and Admin APIs
Authentication
OAuth API account credentials — a store-generated client ID and permanent access token sent in the X-Auth-Token header, limited to the OAuth scopes granted when the account is created (e.g. store_v2_orders, store_v2_products)
Change detection
Webhooks push near-real-time events (store/order/*, store/product/*, store/customer/* and more); polling uses date_modified:min/max filters on Products, Orders, and Customers
Capabilities
read · write · webhooks
Rate limits
OAuth quota refreshes every 30 seconds and varies by plan (about 20,000 requests/hour on Standard and Plus, 60,000 on Pro, higher on Enterprise); the X-Rate-Limit-Requests-Left header reports remaining calls.
Bigcommerce setup guide

Cloudera Data Platform

Integration surface
JDBC/ODBC over Hive and Impala SQL endpoints, plus REST management APIs
Authentication
Kerberos, LDAP, or workload user credentials, often brokered through the Knox gateway
Change detection
Polling via SQL on timestamp or partition columns; no consumer-facing change feed
Capabilities
read · write
Rate limits
Constrained by cluster capacity and admission control rather than API rate limits
How it works

How to connect Bigcommerce to Cloudera Data Platform — 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 Bigcommerce and Cloudera Data Platform 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
    Bigcommerce connected
    Cloudera Data Platform connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Bigcommerce and Cloudera Data Platform 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 · Bigcommerce ⇄ Cloudera Data Platform
    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
    Bigcommerce Cloudera Data Platform
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Bigcommerce and Cloudera Data Platform 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
HIPAA BAA
GDPR
CCPA
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 394 integrations available for Bigcommerce and Cloudera Data Platform.

Popular · 7 of 394
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