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Data warehouse

Connect Databricks to any app with two-way sync.

Two-way sync Databricks across all your CRMs, databases, data warehouses, EDI systems, and AI tools, with custom workflows tailored to your data.

  • 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

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Object catalog

What Stacksync syncs in Databricks.

These objects sync between Databricks and any connected system, with field-level mapping and conflict resolution. Custom fields are picked up from the live schema where Databricks exposes them.

Catalogs
Top level of the Unity Catalog namespace, scoping which schemas a sync can address.
Schemas
Group tables and views; syncs typically target a dedicated schema per source system.
Delta Tables
The primary read and write target; operational data lands here as managed or external tables.
Views
Curated read-only projections used as sync sources for downstream tools.
Materialized Views
Precomputed results read on a schedule for reverse-ETL style syncs.
Volumes
Unity Catalog file storage used for staging bulk loads.
SQL Warehouses
The compute endpoint a sync connects to for query execution.
Change Data Feed
Row-level change records on Delta tables that drive incremental reads.
API surface

How Stacksync connects to Databricks.

The connector runs on Databricks's native API. Stacksync manages authentication, rate limits, retries, and schema changes so your team does not maintain integration code.

Connection
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
Rate limits
Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits

Sync directions

  • Read Supported
  • Write Supported
  • Change data capture Supported
  • Webhooks Not available
What ships with Databricks

Connect Databricks for flexible, real-time data sync.

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

Real-time

Two-way sync

Changes in Databricks instantly reflect across connected systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Databricks 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 record.

Observability

Monitoring

Track your Databricks sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions.

Use cases

What teams run on the Databricks connector.

Databricks is bought by data platform and engineering leadership as the lakehouse consolidating ETL, analytics, and ML workloads. Curated Delta Tables organized under Catalogs and Schemas become the governed source for metrics, features, and model outputs, so integration runs both directions: landing operational data into the lakehouse and pushing computed results back into the operational systems that act on them.

  • Data engineering
  • Analytics engineering
  • ML engineering
  • Data platform teams

  1. Land CRM and ERP records in Delta tables continuously so lakehouse models work from current operational data.

  2. Reverse-sync scored or enriched tables from Databricks back into Salesforce or HubSpot fields.

  3. Keep a Postgres or MySQL operational database mirrored into the lakehouse for analytics without batch exports.

  4. Use Change Data Feed to propagate only changed rows to downstream apps instead of full-table scans.

  5. Serve ML feature outputs computed in Databricks to production apps through a synced operational store.

  6. Push rows from curated Delta Tables (scores, segments, aggregates) into operational databases and SaaS tools so applications act on lakehouse results without hand-built reverse ETL.

All Databricks integrations

Pick the system you need to keep in sync with Databricks. Each page covers the sync setup, field mapping, and common workflows for that pair.

CRM · 48

ERP · 44

Database · 50

Data warehouse · 28

Business productivity · 41

Accounting and finance · 17

How it works

Set up Databricks in minutes, without APIs.

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 with its 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
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Databricks objects to sync — Stacksync auto-detects the schema, 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
    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 database
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Databricks connector FAQ

What can I sync with the Databricks connector?

Databricks's core objects — Catalogs, Schemas, Delta Tables, Views and custom fields — can sync with any of 302 other systems. Every integration is real-time and bidirectional, with field-level mapping and conflict resolution.

How does Stacksync connect to Databricks?

Via SQL over JDBC/ODBC via SQL warehouses, plus a REST API including statement execution, authenticated with Personal access tokens or OAuth machine-to-machine credentials for service principals. Changes are detected as follows — delta Lake Change Data Feed for row-level changes; otherwise incremental polling on watermark columns. Stacksync manages rate limits, retries, and schema changes automatically.

Is the Databricks connector two-way?

Yes. Changes made in Databricks propagate to the connected system and vice versa, in milliseconds. One-way flows are also supported when a direction should stay read-only.

How long does a Databricks integration take to set up?

Most Databricks integrations go live in minutes: authenticate Databricks and the other system, pick objects and fields, and enable the sync. No code and no infrastructure to manage.

Is Databricks data secure in transit?

Stacksync is SOC 2 Type II, ISO 27001, GDPR and HIPAA compliant. Databricks data is encrypted in transit, and a zero-persistent-storage architecture means records are not retained after a sync operation.

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.

Learn more about security
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:

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