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CRM ⇄ Data warehouse

Crustdata to Databricks integration — real-time data sync

Keep Crustdata and Databricks 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 Crustdata and Databricks

Flow Crustdata data into Databricks in real time — no exports, no schedulers, no custom scripts.

Crustdata is a read-only source: Stacksync reads its data in real time and delivers it into Databricks, so Databricks always reflects the current state of Crustdata — without exports, scripts, or schedulers.

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. Tech Stack, Screener Results, Enrichment Responses, Companies from Crustdata land in Databricks as live tables, updated within seconds, and columns computed in Databricks write back to fields in Crustdata. There is no separate ETL and reverse-ETL stack to stitch together and no jobs to babysit.

Common use cases

  • 01 Stream screener results into a warehouse to maintain a living TAM and target-account universe.
  • 02 Append enrichment at lead-capture time so new records arrive scored and routable.
  • 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

Scores and segments back on the record

Lead scores, churn risk, or usage segments computed in Databricks appear as fields in Crustdata, where the people working accounts actually see them.

A single customer view

Join Crustdata'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.

What you can sync between Crustdata and Databricks

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.

Crustdata objects Databricks objects How this pairing syncs
Companies Firmographic records — industry, size, funding, growth signals; read out to enrich CRM accounts and warehouse company tables. Volumes Unity Catalog file storage used for staging bulk loads. Companies is specific to Crustdata and Volumes to Databricks — each maps to any object or custom field on the other side.
People Contact and profile data for decision-makers; read into a CRM or outreach tool to fill missing titles, emails, and LinkedIn profiles. SQL Warehouses The compute endpoint a sync connects to for query execution. People is specific to Crustdata and SQL Warehouses to Databricks — each maps to any object or custom field on the other side.
Headcount and Growth Metrics Time-series employee counts by department and region; read to score accounts on hiring momentum and expansion signals. Change Data Feed Row-level change records on Delta tables that drive incremental reads. Headcount and Growth Metrics is specific to Crustdata and Change Data Feed to Databricks — each maps to any object or custom field on the other side.
Tech Stack Detected technologies per company; read to build segments and route accounts by the tools they already use. Catalogs Top level of the Unity Catalog namespace, scoping which schemas a sync can address. Tech Stack is specific to Crustdata and Catalogs to Databricks — each maps to any object or custom field on the other side.
Screener Results Saved company searches with filter criteria; read on a schedule so target-account lists in the CRM refresh as companies enter the criteria. Schemas Group tables and views; syncs typically target a dedicated schema per source system. Screener Results is specific to Crustdata and Schemas to Databricks — each maps to any object or custom field on the other side.
Enrichment Responses Real-time enrichment lookups keyed by domain or profile URL; read to append fresh firmographic and contact data at form-fill or record-creation time. Delta Tables The primary read and write target; operational data lands here as managed or external tables. Enrichment Responses is specific to Crustdata and Delta Tables to Databricks — each maps to any object or custom field on the other side.

How changes propagate between Crustdata and Databricks

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.

Crustdata Databricks Interval-based propagation

DetectionStacksync polls Crustdata for changes on an incremental schedule, reading only records changed since the previous pass. Pull-based: real-time enrichment endpoints for on-demand lookups plus periodic re-pulls of screeners and datasets.

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

Databricks Crustdata 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.

DeliveryCrustdata does not accept inbound record writes, so this direction carries requests rather than records: Crustdata's output flows back as field updates on the originating Databricks records.

Rate-limit considerations

  • Crustdata: Requests are metered by plan credits and per-minute rate limits; bulk dataset pulls are the efficient path for large refreshes rather than per-record enrichment calls.
  • Databricks: Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits.
What ships with Crustdata ⇄ Databricks

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

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

Real-time

Real-time sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Crustdata or 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 Crustdata or Databricks record.

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Crustdata and Databricks.

How the Crustdata and Databricks connectors work

Crustdata

Integration surface
REST API (JSON)
Authentication
API token — Authorization: Token header issued per workspace
Change detection
Pull-based: real-time enrichment endpoints for on-demand lookups plus periodic re-pulls of screeners and datasets; no webhooks or change feed
Capabilities
read
Rate limits
Requests are metered by plan credits and per-minute rate limits; bulk dataset pulls are the efficient path for large refreshes rather than per-record enrichment calls.

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
How it works

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

    Choose tables

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

Crustdata and Databricks 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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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 348 integrations available for Crustdata and Databricks.

Popular · 6 of 348
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