Databricks to Linnworks integration — real-time, two-way sync

Yes. Stacksync provides a managed, real-time two-way integration between Databricks and Linnworks: authenticate both systems, choose the objects to sync (such as Databricks's Volumes and SQL Warehouses), map fields visually, and changes propagate both ways in milliseconds — no code required.

On the Databricks side: Schemas, Delta Tables, Views, Materialized Views, plus custom fields where Databricks exposes them. On the Linnworks side: Locations, Purchase Orders, Suppliers, Channel Listings. 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 Linnworks: Where Linnworks runs operations: order and supply analysis; Group reporting across systems; Write-back where Linnworks exposes writable fields. Operational records become queryable tables in Databricks, joinable with sales and finance data.

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. Linnworks: REST API. Authentication: Application credentials and an install token exchanged for a session token. Stacksync manages authentication, retries, and rate limits on both sides.

Databricks: Unity Catalog imposes a three-level namespace (catalog.schema.table) that governs access across workspaces. Linnworks: The Linnworks API uses a token-exchange model: application credentials plus a per-account install token are exchanged for a session token that authorizes subsequent calls. Stacksync's field mapping accounts for these differences between Databricks and Linnworks without custom code.