Real-time
Two-way sync
Changes in Databricks or Front instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ Business productivity
Databricks to Front integration — real-time, two-way sync
Keep Databricks and Front 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 Front
Get the data locked inside Front into Databricks as live tables, and send results back where Front can use them, without writing a pipeline.
Whatever Front 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 Teammates, Channels, Conversations, Messages from Front 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 Front where the tool can use them.
Common use cases
- Sync conversations, messages, and tags into Postgres for response-time and volume analytics across inboxes.
- Write CRM account tier, owner, and renewal data into Front contact and account custom fields so it shows next to the conversation.
- 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.
Cross-tool reporting
Combine Front's data with data from every other synced system to answer questions no single tool can.
Where Front accepts updates: operational write-back
Segments, scores, or reference values computed in Databricks sync back onto records in Front, putting analysis where the work happens.
History that outlives the tool
A continuously synced copy in Databricks preserves a queryable record even as data ages out of Front or gets changed inside it.
What you can sync between Databricks and Front
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 | Front objects | |
|---|---|---|
| Catalogs Top level of the Unity Catalog namespace, scoping which schemas a sync can address. | Tags Labels applied to conversations; drive routing and category-level analytics. | |
| Schemas Group tables and views; syncs typically target a dedicated schema per source system. | Teammates Agents; used for ownership mapping and workload reporting. | |
| Delta Tables The primary read and write target; operational data lands here as managed or external tables. | Channels Connected addresses (email, SMS, chat); define where messages originate and send from. | |
| Views Curated read-only projections used as sync sources for downstream tools. | Conversations The central threaded unit that messages, comments, and tags attach to; synced for support analytics. | |
| Materialized Views Precomputed results read on a schedule for reverse-ETL style syncs. | Messages Inbound and outbound emails, chats, and SMS within a conversation; read out for response-time reporting. | |
| Volumes Unity Catalog file storage used for staging bulk loads. | Comments Internal team notes on conversations; usually read-only in syncs. |
What ships with Databricks ⇄ Front
Connect Databricks and Front for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Databricks–Front connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Databricks or Front 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 Front record.
Observability
Monitoring
Track your Databricks ⇄ Front 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 Front.
How the Databricks and Front 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
Front
- Integration surface
- REST API (Core API)
- Authentication
- OAuth authorization via the Stacksync UI ("Connections" > "create new connection" > "Front" > "Authorize") — no coding required
- Change detection
- Application webhooks and rule-triggered webhooks, with the events endpoint available for polling
- Capabilities
- read · write · webhooks
- Rate limits
- Request limits vary by plan.
How it works
How to connect Databricks to Front — 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 Front 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
Front
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Databricks and Front 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 ⇄ FrontCustomers 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 FrontCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Databricks and Front integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Databricks and Front: authenticate both systems, choose the objects to sync (such as Databricks's Catalogs and Schemas), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Front: The data model is conversation-centric: messages, comments, and tags attach to conversations rather than tickets, which shapes how support data maps to relational tables. Databricks: Delta Lake's Change Data Feed records row-level inserts, updates, and deletes, enabling incremental sync without full scans. Stacksync's field mapping accounts for these differences between Databricks and Front without custom code.
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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 Front records are not retained after a sync operation.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed Databricks and Front connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Databricks–Front integration in-house.
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Yes — Stacksync ships production-grade connectors for both Databricks and Front. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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Change detection on Databricks: Delta Lake Change Data Feed for row-level changes; otherwise incremental polling on watermark columns. On Front: Application webhooks and rule-triggered webhooks, with the events endpoint available for polling. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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 Front.
Popular · 8 of 386
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Databricks ⇄ eClinicalWorks -
Databricks ⇄ Full Enrich -
Databricks ⇄ Google Sheets -
Databricks ⇄ Klaviyo -
Front ⇄ Apache Hive -
Front ⇄ Apache Impala -
Front ⇄ Apache Kylin -
Front ⇄ Apache Pinot
No integrations match .
