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Data warehouse ⇄ CRM

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

Keep Databricks and Gladly 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

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Why teams connect Databricks and Gladly

Sync Gladly into Databricks continuously and push warehouse results back onto CRM records, one two-way connection instead of two pipelines.

The CRM feeds the warehouse and the warehouse should feed the CRM: relationship data flows one way, and computed scores, segments, and customer context flow back. Most teams build the first half as a batch pipeline and never quite get to the second.

Stacksync does both with one connection. Conversations, Conversation items, Agents, Topics from Gladly land in Databricks as live tables, updated within seconds, and columns computed in Databricks write back to fields in Gladly. There is no separate ETL and reverse-ETL stack to stitch together and no jobs to babysit.

Common use cases

  • Push conversation outcomes into a CRM so account teams see support context on their accounts.
  • Sync Gladly customer profiles with an order database so agents see purchase history and profile updates flow back.
  • Use Change Data Feed to propagate only changed rows to downstream apps instead of full-table scans.
  • Serve ML feature outputs computed in Databricks to production apps through a synced operational store.

A single customer view

Join Gladly's relationship data with billing, product, and support data in Databricks to build the customer picture the CRM alone cannot hold.

Cleanup that sticks

Deduplication and normalization done in Databricks can be written back, so warehouse-side cleanup actually fixes the CRM.

CRM analytics on live data

Accounts, contacts, and activity from Gladly are queryable in Databricks moments after they change, so dashboards stop lagging the reality they describe.

What you can sync between Databricks and Gladly

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 Gladly objects
Volumes Unity Catalog file storage used for staging bulk loads. Topics Categorization applied to conversations; the key dimension for contact-driver reporting.
SQL Warehouses The compute endpoint a sync connects to for query execution. Tasks Follow-up work items created from external triggers or synced for workload reporting.
Change Data Feed Row-level change records on Delta tables that drive incremental reads. Customer profiles The central entity; merges identifiers like email, phone, and order IDs, which syncs use for matching.
Catalogs Top level of the Unity Catalog namespace, scoping which schemas a sync can address. Conversations Each customer's continuous timeline; status and outcomes sync to CRMs and warehouses.
Schemas Group tables and views; syncs typically target a dedicated schema per source system. Conversation items Individual messages across voice, SMS, chat, and email attached to the conversation.
Delta Tables The primary read and write target; operational data lands here as managed or external tables. Agents User records used to attribute work in CX analytics.
What ships with Databricks ⇄ Gladly

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Databricks or Gladly 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 Gladly record.

Observability

Monitoring

Track your Databricks ⇄ Gladly 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 Gladly.

How the Databricks and Gladly 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

Gladly

Integration surface
REST API
Authentication
API tokens used with basic authentication tied to an agent email
Change detection
Webhook event subscriptions for conversation and customer events, supplemented by polling and report exports
Capabilities
read · write · webhooks
Rate limits
Subject to the platform's API rate limits
How it works

How to connect Databricks to Gladly — 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 Gladly 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
    Gladly connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Databricks and Gladly 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 ⇄ Gladly
    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 Gladly
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Databricks and Gladly integration FAQ

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.

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

Related integrations

Every pair below is a real-time, two-way sync. Search all 386 integrations available for Databricks and Gladly.

Popular · 8 of 386
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