Two-way sync
Changes in Databricks or Zendesk instantly reflect in both systems. No stale data, no manual imports.
Keep Databricks and Zendesk 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 Zendesk 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 Attachments, Ticket Forms, Tickets, Tickets Comments from Zendesk into tables in Databricks continuously, handling schema, rate limits, and retries. Because the sync is bi-directional, results computed in Databricks can also be written back into fields in Zendesk where the tool can use them.
Combine Zendesk's data with data from every other synced system to answer questions no single tool can.
Segments, scores, or reference values computed in Databricks sync back onto records in Zendesk, putting analysis where the work happens.
A continuously synced copy in Databricks preserves a queryable record even as data ages out of Zendesk or gets changed inside it.
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 | Zendesk objects | |
|---|---|---|
| SQL Warehouses The compute endpoint a sync connects to for query execution. | Tickets Comments Synced with incremental and full sync per the Stacksync docs. | |
| Change Data Feed Row-level change records on Delta tables that drive incremental reads. | Users End users and agents; matched to CRM contacts to keep requester data consistent. | |
| Catalogs Top level of the Unity Catalog namespace, scoping which schemas a sync can address. | Organizations Company groupings for users; typically kept aligned with CRM accounts. | |
| Schemas Group tables and views; syncs typically target a dedicated schema per source system. | Attachments Synced with incremental and full sync per the Stacksync docs. | |
| Delta Tables The primary read and write target; operational data lands here as managed or external tables. | Ticket Forms Synced with incremental and full sync per the Stacksync docs. | |
| Views Curated read-only projections used as sync sources for downstream tools. | Tickets The central work object; synced to databases for SLA and volume reporting or mirrored into engineering tools. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Databricks–Zendesk connection.
Changes in Databricks or Zendesk instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Databricks or Zendesk data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Databricks or Zendesk record.
Track your Databricks ⇄ Zendesk sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Databricks and Zendesk.
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 Databricks and Zendesk 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 Databricks and Zendesk 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 Databricks and Zendesk: authenticate both systems, choose the objects to sync (such as Databricks's SQL Warehouses and Change Data Feed), map fields visually, and changes propagate both ways in milliseconds — no code required.
On the Zendesk side: Attachments, Ticket Forms, Tickets, Tickets Comments, plus custom fields where Zendesk exposes them. On the Databricks side: Views, Materialized Views, Volumes, SQL Warehouses. 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 Databricks and Zendesk: Cross-tool reporting; Where Zendesk accepts updates: operational write-back; History that outlives the tool. Combine Zendesk's data with data from every other synced system to answer questions no single tool can.
Databricks: 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. Zendesk: REST API. Authentication: OAuth app authorization: enter your Zendesk subdomain (from {sub_domain_name}.zendesk.com) in Stacksync Connections and click "Authorize App". Stacksync manages authentication, retries, and rate limits on both sides.
Zendesk: Ticket comments cannot be edited after creation, so downstream copies of conversations only ever append. Databricks: Unity Catalog imposes a three-level namespace (catalog.schema.table) that governs access across workspaces. Stacksync's field mapping accounts for these differences between Databricks and Zendesk without custom code.
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 Databricks and Zendesk.