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Data warehouse ⇄ Business productivity

Databricks to Full Enrich integration — real-time, two-way sync

Keep Databricks and Full Enrich 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 Full Enrich

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

Whatever Full Enrich 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 Contacts, Enrichment results, Emails, Phone numbers from Full Enrich 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 Full Enrich where the tool can use them.

Common use cases

  • 01 Run waterfall enrichment over warehouse lead lists before importing them into outbound sequencers.
  • 02 Backfill missing phone numbers on aging CRM records on a schedule.
  • 03 Use Change Data Feed to propagate only changed rows to downstream apps instead of full-table scans.
  • 04 Serve ML feature outputs computed in Databricks to production apps through a synced operational store.

Common sync patterns

Where Full Enrich accepts updates: operational write-back

Segments, scores, or reference values computed in Databricks sync back onto records in Full Enrich, 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 Full Enrich or gets changed inside it.

Analytics on Full Enrich's data

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

What you can sync between Databricks and Full Enrich

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 Full Enrich objects How this pairing syncs
Views Curated read-only projections used as sync sources for downstream tools. Credits Account balance consumed on successful finds; monitored to pace sync jobs. Views is specific to Databricks and Credits to Full Enrich — 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. Enrichment requests Submitted batches of contacts to enrich; processed asynchronously by the waterfall. Materialized Views is specific to Databricks and Enrichment requests to Full Enrich — each maps to any object or custom field on the other side.
Volumes Unity Catalog file storage used for staging bulk loads. Contacts The person inputs (name plus company or domain) sent for enrichment. Volumes is specific to Databricks and Contacts to Full Enrich — each maps to any object or custom field on the other side.
SQL Warehouses The compute endpoint a sync connects to for query execution. Enrichment results Completed records fetched by request ID or delivered via webhook. SQL Warehouses is specific to Databricks and Enrichment results to Full Enrich — 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. Emails Returned addresses with verification status, written back to the CRM or database. Change Data Feed is specific to Databricks and Emails to Full Enrich — 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. Phone numbers Returned mobile and direct-dial numbers from the provider waterfall. Catalogs is specific to Databricks and Phone numbers to Full Enrich — each maps to any object or custom field on the other side.

How changes propagate between Databricks and Full Enrich

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 Full Enrich 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 Full Enrich through its API, with automatic retries and rate-limit backoff.

Full Enrich Databricks Sub-second propagation

DetectionFull Enrich notifies Stacksync of record changes through webhook events. Webhook callbacks when enrichment batches complete, with polling of result endpoints as a fallback.

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.
  • Full Enrich: Subject to the platform's API rate limits and per-batch size constraints.
What ships with Databricks ⇄ Full Enrich

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Databricks or Full Enrich 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 Full Enrich record.

Observability

Monitoring

Track your Databricks ⇄ Full Enrich 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 Full Enrich.

How the Databricks and Full Enrich 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

Full Enrich

Integration surface
REST API with asynchronous bulk enrichment endpoints
Authentication
API key (Bearer token)
Change detection
Webhook callbacks when enrichment batches complete, with polling of result endpoints as a fallback
Capabilities
read · write · webhooks
Rate limits
Subject to the platform's API rate limits and per-batch size constraints
How it works

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

    Choose tables

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

Databricks and Full Enrich 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.

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 430 integrations available for Databricks and Full Enrich.

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