Two-way sync
Changes in Apache Druid or Orderful instantly reflect in both systems. No stale data, no manual imports.
Keep Apache Druid and Orderful in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Whatever Orderful is used for, it accumulates data the rest of the company wants to analyze, and that data usually sits behind an API rather than in the warehouse. Building and babysitting an extraction pipeline is the tax most teams pay for it.
Stacksync syncs Relationships, Validation guidelines, Acknowledgments, Webhook events from Orderful into tables in Apache Druid continuously, handling schema, rate limits, and retries. Because the sync is bi-directional, results computed in Apache Druid can also be written back into fields in Orderful where the tool can use them.
A continuously synced copy in Apache Druid preserves a queryable record even as data ages out of Orderful or gets changed inside it.
Records and events from Orderful land in Apache Druid as queryable tables, current within seconds and ready to join with the rest of the warehouse.
Combine Orderful's data with data from every other synced system to answer questions no single tool can.
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.
| Apache Druid objects | Orderful objects | |
|---|---|---|
| Ingestion Supervisors Long-running specs that pull from streams like Kafka; the write path into Druid. | Webhook events Push notifications for inbound documents and transaction status changes | |
| Lookups Key-value mappings joined at query time, refreshable from external systems. | Transactions EDI documents such as 850 purchase orders, 810 invoices, and 856 ship notices, represented as JSON | |
| Tasks Batch ingestion and compaction jobs monitored during data loads. | Trading partners The retailers, carriers, and suppliers a company exchanges documents with | |
| Datasources The table-like unit of storage and querying, the main target of reads and ingestion. | Relationships Active partner connections per transaction type that govern what can be sent and received | |
| Segments Time-partitioned immutable files that hold datasource data; ingestion produces them. | Validation guidelines Partner-specific rules transactions are checked against before delivery | |
| Dimensions String and categorical columns used for filtering and grouping in synced queries. | Acknowledgments 997 functional acknowledgments confirming receipt of transmitted documents |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Druid–Orderful connection.
Changes in Apache Druid or Orderful instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Apache Druid or Orderful data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Apache Druid or Orderful record.
Track your Apache Druid ⇄ Orderful sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Apache Druid and Orderful.
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 Apache Druid and Orderful 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 Apache Druid and Orderful 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 Apache Druid and Orderful: authenticate both systems, choose the objects to sync (such as Apache Druid's Ingestion Supervisors and Lookups), map fields visually, and changes propagate both ways in milliseconds — no code required.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Apache Druid and Orderful connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Apache Druid–Orderful integration in-house.
Yes — Stacksync ships production-grade connectors for both Apache Druid and Orderful. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
Change detection on Apache Druid: Not applicable for reads out (polling by time interval); data enters Druid through streaming or batch ingestion rather than row updates. On Orderful: Webhooks push inbound transactions and status events; polling available as fallback. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Orderful side: Relationships, Validation guidelines, Acknowledgments, Webhook events, plus custom fields where Orderful 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.
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 Apache Druid and Orderful.