Real-time
Two-way sync
Changes in Anaplan or Databricks instantly reflect in both systems. No stale data, no manual imports.
Accounting and finance ⇄ Data warehouse
Anaplan to Databricks integration — real-time, two-way sync
Keep Anaplan and Databricks 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
Case study
Migrated from Mulesoft
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Migrated from Matillion
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Migrated from Fivetran
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Migrated from Celigo
Why teams connect Anaplan and Databricks
Land the financial records from Anaplan in Databricks continuously, and write results back, without building or maintaining a pipeline.
Finance data belongs in the warehouse: revenue, invoices, payments, and customers joined with everything else the business measures. Getting it there usually means an extraction pipeline that breaks quietly and delivers yesterday's numbers.
Stacksync syncs Models, Modules, Line Items, Lists from Anaplan into tables in Databricks in real time, and the connection works in both directions: values computed in Databricks can be written back to fields in Anaplan where you want them operational. Schema changes are handled, API limits are managed, and the sync is something you configure rather than code you maintain.
Common use cases
- Export forecast versions to a warehouse for variance reporting against actuals.
- Load actuals from an ERP or warehouse into Anaplan modules so forecasts start from current financials.
- Serve ML feature outputs computed in Databricks to production apps through a synced operational store.
- Land CRM and ERP records in Delta tables continuously so lakehouse models work from current operational data.
Write-back of computed fields
Scores or segments computed in Databricks, like payment-risk flags or customer tiers, sync back onto records in Anaplan where the finance team can act on them.
Queryable history for audit and reconciliation
A continuously synced copy in Databricks gives you a durable, queryable record of financial data for month-end and audit questions.
Finance analytics without ETL
Invoices, payments, and customer records from Anaplan arrive in Databricks as queryable tables, current within seconds instead of a day behind.
What you can sync between Anaplan and Databricks
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.
| Anaplan objects | Databricks objects | |
|---|---|---|
| Cell Data Individual intersections readable and writable through the transactional API. | SQL Warehouses The compute endpoint a sync connects to for query execution. | |
| Models The planning workspaces that contain all data; syncs target a specific model. | Change Data Feed Row-level change records on Delta tables that drive incremental reads. | |
| Modules Multidimensional grids of line items where plan data lives; the main read/write surface. | Catalogs Top level of the Unity Catalog namespace, scoping which schemas a sync can address. | |
| Line Items The measures within a module, mapped to columns or metrics in syncs. | Schemas Group tables and views; syncs typically target a dedicated schema per source system. | |
| Lists Dimension members (accounts, products, cost centers) synced from master data systems. | Delta Tables The primary read and write target; operational data lands here as managed or external tables. | |
| List Items Individual dimension members created or updated from external systems of record. | Views Curated read-only projections used as sync sources for downstream tools. |
What ships with Anaplan ⇄ Databricks
Connect Anaplan and Databricks for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Anaplan–Databricks connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Anaplan or Databricks 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 Anaplan or Databricks record.
Observability
Monitoring
Track your Anaplan ⇄ Databricks sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Anaplan and Databricks.
How the Anaplan and Databricks connectors work
Anaplan
- Integration surface
- REST APIs: a Bulk API that runs predefined import/export actions and a transactional API for model metadata and cell data
- Authentication
- Token-based sessions obtained via basic authentication, CA certificates, or OAuth 2.0 through Anaplan's authentication service
- Change detection
- Polling and scheduled export actions; the platform does not expose change events
- Capabilities
- read · write
- Rate limits
- Subject to the platform's API rate limits; large data movements are designed to run through bulk actions
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
How it works
How to connect Anaplan to Databricks — 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 Anaplan and Databricks with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Anaplan
connected
Databricks
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Anaplan and Databricks 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 · Anaplan ⇄ DatabricksCustomers 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.
Anaplan DatabricksCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Anaplan and Databricks integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Anaplan and Databricks: authenticate both systems, choose the objects to sync (such as Anaplan's Cell Data and Models), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Anaplan: Anaplan's in-memory engine recalculates dependent line items on write, so loads propagate through model formulas immediately. Databricks: Delta Lake's Change Data Feed records row-level inserts, updates, and deletes, enabling incremental sync without full scans. Stacksync's field mapping accounts for these differences between Anaplan and Databricks without custom code.
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Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means Anaplan and Databricks records are not retained after a sync operation.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed Anaplan and Databricks connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Anaplan–Databricks integration in-house.
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Yes — Stacksync ships production-grade connectors for both Anaplan and Databricks. 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 Anaplan: Polling and scheduled export actions; the platform does not expose change events. On Databricks: Delta Lake Change Data Feed for row-level changes; otherwise incremental polling on watermark columns. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
SECURITY
Security teams love 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.
SOC 2 type II
ISO 27001
HIPAA BAA
GDPR
CCPA
CSA STAR
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
Every pair below is a real-time, two-way sync. Search all 386 integrations available for Anaplan and Databricks.
Popular · 8 of 386
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Anaplan ⇄ Apache Doris -
Anaplan ⇄ Apache Druid -
Anaplan ⇄ Apache Hive -
Anaplan ⇄ Apache Impala -
Databricks ⇄ Stripe -
Databricks ⇄ Rillet -
Databricks ⇄ Workday -
Databricks ⇄ Chargebee
No integrations match .
