Real-time
Two-way sync
Changes in Databricks or Deposco instantly reflect in both systems. No stale data, no manual imports.
.png){kind=small}
Data warehouse ⇄ ERP
Databricks to Deposco integration — real-time, two-way sync
Keep Databricks and Deposco 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
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Databricks and Deposco
Put Deposco's records in Databricks as live tables for reporting and analysis, without extract jobs, and write results back where Deposco can use them.
ERP data is some of the most asked-for data in the warehouse and some of the hardest to get: the record types are many, the APIs are strict, and extract jobs are brittle. Whether Deposco carries financials, operations, workforce data, or all three, the analysis belongs in Databricks next to everything else the company measures.
Stacksync syncs Warehouses / Locations, Customers, Items / SKUs, Inventory from Deposco into tables in Databricks continuously, managing API limits and schema drift along the way. The connection is bi-directional, so values computed in Databricks can be written back to fields in Deposco where that is useful.
Common use cases
- 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.
- Push sales orders from an ERP or e-commerce platform into Deposco for warehouse fulfillment.
- Sync available-to-promise inventory to storefronts and marketplaces to prevent overselling.
Where Deposco is the HR system of record: workforce analytics
Worker and organization data syncs into Databricks for headcount, cost, and planning analysis alongside other company data.
Where Deposco runs operations: order and supply analysis
Operational records become queryable tables in Databricks, joinable with sales and finance data.
Group reporting across systems
Combine Deposco's records with data synced from other systems in Databricks for consolidated views no single system can produce.
What you can sync between Databricks and Deposco
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 | Deposco objects | |
|---|---|---|
| Change Data Feed Row-level change records on Delta tables that drive incremental reads. | Customers Ship-to parties referenced on orders and shipments. | |
| Catalogs Top level of the Unity Catalog namespace, scoping which schemas a sync can address. | Items / SKUs Product master records that fulfillment operations pick and ship against. | |
| Schemas Group tables and views; syncs typically target a dedicated schema per source system. | Inventory On-hand and available quantities by warehouse and location, read frequently by storefront syncs. | |
| Delta Tables The primary read and write target; operational data lands here as managed or external tables. | Sales orders Orders flowing in from ERP or e-commerce systems for fulfillment. | |
| Views Curated read-only projections used as sync sources for downstream tools. | Shipments Outbound shipment and tracking records synced back to order-origin systems. | |
| Materialized Views Precomputed results read on a schedule for reverse-ETL style syncs. | Purchase orders / ASNs Inbound expectations used to plan receiving. |
What ships with Databricks ⇄ Deposco
Connect Databricks and Deposco for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Databricks–Deposco connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Databricks or Deposco 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 Databricks or Deposco record.
Observability
Monitoring
Track your Databricks ⇄ Deposco sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Databricks and Deposco.
How the Databricks and Deposco connectors work
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
Deposco
- Integration surface
- REST API plus file-based interfaces (EDI and flat file) common to WMS integrations
- Authentication
- API credentials issued per integration (API key or basic authentication)
- Change detection
- Polling on order and inventory endpoints, subject to the platform's integration patterns
- Capabilities
- read · write
- Rate limits
- Subject to the platform's API rate limits
How it works
How to connect Databricks to Deposco — 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 Databricks and Deposco with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Databricks
connected
Deposco
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Databricks and Deposco 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 · Databricks ⇄ DeposcoCustomers 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.
Databricks DeposcoCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Databricks and Deposco integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Databricks and Deposco: authenticate both systems, choose the objects to sync (such as Databricks's Change Data Feed and Catalogs), map fields visually, and changes propagate both ways in milliseconds — no code required.
-
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. Deposco: REST API plus file-based interfaces (EDI and flat file) common to WMS integrations. Authentication: API credentials issued per integration (API key or basic authentication). Stacksync manages authentication, retries, and rate limits on both sides.
-
Databricks: Delta Lake's Change Data Feed records row-level inserts, updates, and deletes, enabling incremental sync without full scans. Deposco: Integration runs through Deposco's Bright Socket layer, which combines API access with EDI and file-based data exchange for trading partners and carriers, as is typical for warehouse management systems. Stacksync's field mapping accounts for these differences between Databricks and Deposco without custom code.
-
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 Databricks and Deposco records are not retained after a sync operation.
-
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Databricks and Deposco connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Databricks–Deposco integration in-house.
-
Yes — Stacksync ships production-grade connectors for both Databricks and Deposco. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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 Databricks and Deposco.
Popular · 8 of 386
-
Databricks ⇄ Microsoft Dynamics GP - Databricks ⇄ Microsoft Dynamics NAV
-
Databricks ⇄ Plex ERP -
Databricks ⇄ QAD ERP -
Deposco ⇄ Dremio -
Deposco ⇄ Exasol -
Deposco ⇄ Firebolt -
Deposco ⇄ Google Cloud Platform
No integrations match .
