Two-way sync
Changes in Anaplan or Apache Druid instantly reflect in both systems. No stale data, no manual imports.
Keep Anaplan and Apache Druid in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
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 Modules, Line Items, Lists, List Items from Anaplan into tables in Apache Druid in real time, and the connection works in both directions: values computed in Apache Druid 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.
A continuously synced copy in Apache Druid gives you a durable, queryable record of financial data for month-end and audit questions.
Invoices, payments, and customer records from Anaplan arrive in Apache Druid as queryable tables, current within seconds instead of a day behind.
Analysts combine Anaplan's financial records with product, marketing, or operational data already in Apache Druid for reporting the finance system cannot do alone.
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 | Apache Druid objects | |
|---|---|---|
| Processes Ordered bundles of actions run as a unit during scheduled syncs. | Tasks Batch ingestion and compaction jobs monitored during data loads. | |
| Cell Data Individual intersections readable and writable through the transactional API. | Datasources The table-like unit of storage and querying, the main target of reads and ingestion. | |
| Models The planning workspaces that contain all data; syncs target a specific model. | Segments Time-partitioned immutable files that hold datasource data; ingestion produces them. | |
| Modules Multidimensional grids of line items where plan data lives; the main read/write surface. | Dimensions String and categorical columns used for filtering and grouping in synced queries. | |
| Line Items The measures within a module, mapped to columns or metrics in syncs. | Metrics Numeric columns, often pre-aggregated at ingestion via rollup. | |
| Lists Dimension members (accounts, products, cost centers) synced from master data systems. | Ingestion Supervisors Long-running specs that pull from streams like Kafka; the write path into Druid. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Anaplan–Apache Druid connection.
Changes in Anaplan or Apache Druid instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Anaplan or Apache Druid data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Anaplan or Apache Druid record.
Track your Anaplan ⇄ Apache Druid sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Anaplan and Apache Druid.
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.
Authenticate Anaplan and Apache Druid with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Pick the Anaplan and Apache Druid 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.
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Yes. Stacksync provides a managed, real-time two-way integration between Anaplan and Apache Druid: authenticate both systems, choose the objects to sync (such as Anaplan's Processes and Cell Data), map fields visually, and changes propagate both ways in milliseconds — no code required.
Change detection on Anaplan: Polling and scheduled export actions; the platform does not expose change events. On Apache Druid: Not applicable for reads out (polling by time interval); data enters Druid through streaming or batch ingestion rather than row updates. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Anaplan side: Modules, Line Items, Lists, List Items, plus custom fields where Anaplan exposes them. On the Apache Druid side: Lookups, Tasks, Datasources, Segments. Stacksync auto-detects both schemas and converts types between the two systems.
Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
Common patterns for Anaplan and Apache Druid: Queryable history for audit and reconciliation; Finance analytics without ETL; Revenue joined with everything else. A continuously synced copy in Apache Druid gives you a durable, queryable record of financial data for month-end and audit questions.
Anaplan: 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. Apache Druid: REST API (SQL over HTTP and native JSON queries); JDBC via Avatica. Authentication: Deployment-dependent: basic authentication or an authenticator extension; often fronted by a proxy. Stacksync manages authentication, retries, and rate limits on both sides.
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.
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Securely connects to your systems with:
Every pair below is a real-time, two-way sync. Search all 386 integrations available for Anaplan and Apache Druid.