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Data warehouse ⇄ Business productivity

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

Keep Databricks and Monday in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Databricks and Monday

Get the data locked inside Monday into Databricks as live tables, and send results back where Monday can use them, without writing a pipeline.

Whatever Monday 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 Subitems, Column values, Groups, Updates from Monday 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 Monday where the tool can use them.

Common use cases

  • 01 Two-way sync of Items and their Column values between a monday.com board and Postgres so ops teams work in SQL while project owners stay in monday.com.
  • 02 Write closed deals or provisioning records from a CRM or ERP into monday.com Items to kick off delivery and onboarding boards.
  • 03 Serve ML feature outputs computed in Databricks to production apps through a synced operational store.
  • 04 Land CRM and ERP records in Delta tables continuously so lakehouse models work from current operational data.

Common sync patterns

History that outlives the tool

A continuously synced copy in Databricks preserves a queryable record even as data ages out of Monday or gets changed inside it.

Analytics on Monday's data

Records and events from Monday land in Databricks as queryable tables, current within seconds and ready to join with the rest of the warehouse.

Cross-tool reporting

Combine Monday's data with data from every other synced system to answer questions no single tool can.

What you can sync between Databricks and Monday

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 Monday objects How this pairing syncs
Views Curated read-only projections used as sync sources for downstream tools. Updates Comment and activity threads attached to items; read out into a database for reporting or written back as notes. Views is specific to Databricks and Updates to Monday — each maps to any object or custom field on the other side.
Materialized Views Precomputed results read on a schedule for reverse-ETL style syncs. Users Account members referenced by people columns; read to resolve owner and assignee IDs to names and emails. Materialized Views is specific to Databricks and Users to Monday — each maps to any object or custom field on the other side.
Volumes Unity Catalog file storage used for staging bulk loads. Workspaces Top-level containers that hold boards; used to scope which boards a given sync covers. Volumes is specific to Databricks and Workspaces to Monday — each maps to any object or custom field on the other side.
SQL Warehouses The compute endpoint a sync connects to for query execution. Boards Table-like containers that hold items; each board maps to a synced table, and its columns define the field mapping. SQL Warehouses is specific to Databricks and Boards to Monday — each maps to any object or custom field on the other side.
Change Data Feed Row-level change records on Delta tables that drive incremental reads. Items Rows within a board and the primary record; synced two-way and created, updated, archived, or deleted via GraphQL mutations. Change Data Feed is specific to Databricks and Items to Monday — each maps to any object or custom field on the other side.
Catalogs Top level of the Unity Catalog namespace, scoping which schemas a sync can address. Subitems Nested rows under items, stored on a separate hidden board; synced as a child table linked to the parent item. Catalogs is specific to Databricks and Subitems to Monday — each maps to any object or custom field on the other side.

How changes propagate between Databricks and Monday

Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.

Databricks Monday Sub-second propagation

DetectionChanges in Databricks are captured at the source via change data capture — no polling loop against its API. Delta Lake Change Data Feed for row-level changes.

DeliveryEach detected change is written to Monday through its API, with automatic retries and rate-limit backoff.

Monday Databricks Sub-second propagation

DetectionMonday notifies Stacksync of record changes through webhook events. Board-scoped webhooks (create_item, change_column_value, item_deleted, and similar) for real-time events.

DeliveryEach detected change is applied to Databricks as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Databricks: Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits.
  • Monday: Complexity-budget limits: a single query caps at 5M complexity points and ~10M points/min per user token (1M on trial/free) over a sliding 60s window.
What ships with Databricks ⇄ Monday

Connect Databricks and Monday for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Databricks–Monday connection.

Real-time

Two-way sync

Changes in Databricks or Monday instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Databricks or Monday 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 Monday record.

Observability

Monitoring

Track your Databricks ⇄ Monday 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 Monday.

How the Databricks and Monday 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

Monday

Integration surface
GraphQL API (single endpoint, api.monday.com/v2)
Authentication
OAuth 2.0 for installed apps, or a per-user personal API token (admin/member scope); a date-based API version is sent via request header
Change detection
Board-scoped webhooks (create_item, change_column_value, item_deleted, and similar) for real-time events; polling falls back to the item updated_at field
Capabilities
read · write · webhooks
Rate limits
Complexity-budget limits: a single query caps at 5M complexity points and ~10M points/min per user token (1M on trial/free) over a sliding 60s window
Monday setup guide
How it works

How to connect Databricks to Monday — 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.

  1. 01

    Connect your apps

    Authenticate Databricks and Monday with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Databricks connected
    Monday connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Databricks and Monday 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.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Databricks ⇄ Monday
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Databricks Monday
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Databricks and Monday integration FAQ

SECURITY

Security teams trust 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.

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→ 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:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 555 integrations available for Databricks and Monday.

Popular · 8 of 555
All Databricks integrations All Monday integrations Browse all integrations
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