RapidCanvas

RapidCanvas + Databricks

  • Lakehouse platform
  • Direct today

RapidCanvas ships Databricks ingestion as versioned Asset Bundles, keeps Unity Catalog in charge, and reads Delta tables through Databricks SQL for agents and applications.

Where a customer runs its lakehouse on Databricks, RapidCanvas works with it rather than beside it. Our Hybrid Approach™, an agentic platform paired with expert-in-the-loop delivery, packages ingestion as Databricks Asset Bundles versioned with the rest of the solution, keeps Unity Catalog as the governance boundary, and reads Delta tables through Databricks SQL to feed agents and applications.

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2

Databricks use cases documented

3

Medallion layers: bronze, silver, gold Delta tables

4

Databricks features used: bundles, catalog, SQL, Model Serving

How it fits

  • Ingestion notebooks and jobs are defined in a Databricks Asset Bundle and deployed from the solution repository with the Databricks CLI, reviewed like any other code.
  • Catalogs, schemas and volumes remain the landing zone and the permission boundary; RapidCanvas queries respect the grants already in place.
  • RapidCanvas services call Databricks SQL and Model Serving endpoints to bring gold Delta tables and models into agents and Data Apps.

Why Databricks customers choose this

  • Ingestion ships as versioned, reviewed code, not a hand-built job in the workspace.
  • Unity Catalog governance stays intact while RapidCanvas adds the delivery and application layer.
  • Models already running on Databricks Model Serving power agents and Data Apps directly.

Databricks holds the lakehouse and Unity Catalog's governance. RapidCanvas ships ingestion as code and turns Delta tables into agents and Data Apps on top of it.

PartnershipDirect engagement todayNo formal Databricks partner listing in place
Reference Architecture

How RapidCanvas Builds on Databricks

RapidCanvas ships ingestion as a Databricks Asset Bundle, keeps Unity Catalog as the governance boundary, and reads Delta tables through Databricks SQL for agents and applications.

The same three-lane shape recurs across both use cases: Business, RapidCanvas, and Databricks.

Built to keep Unity Catalog in charge, not bypass it.

Code, Not Manual Jobs

Ingestion notebooks and jobs are defined in a Databricks Asset Bundle and deployed from the solution repository with the Databricks CLI, reviewed like any other code.

Unity Catalog Stays Governance

Catalogs, schemas and volumes remain the landing zone and the permission boundary; RapidCanvas queries respect the grants already in place.

Agents Read, Not Replace

RapidCanvas services call Databricks SQL and Model Serving endpoints to bring gold Delta tables and models into agents and Data Apps.

Use Cases

2 Use Cases on Databricks

Customer names are withheld. Every story below is a real RapidCanvas deployment, verified against the delivered code.

Telecommunications, Latin America

A Regulatory Registry Pipeline Shipped As Code

  • Databricks Asset Bundles
  • Databricks Jobs
  • Unity Catalog
  • Delta tables

A telecommunications operator had to scrub every outbound campaign against a national do-not-call registry that arrives irregularly as dozens of spreadsheet files with no version marker, then cross-check the result against a subscriber base. RapidCanvas built a bronze, silver, gold pipeline deployed as a Databricks Asset Bundle, triggered automatically when a new file lands in a Unity Catalog volume. The pipeline deduplicates millions of phone numbers under an explicit rule, logs every rejection with a reason, and produces the campaign-ready tables the operator's systems consume.

A file-triggered Databricks pipeline deduplicates millions of registry rows before every campaign.
Telecommunications, Latin America

An Agent Pattern Ready For Live Databricks Data

  • Databricks SQL Statement Execution API
  • Databricks Model Serving

Sales agents need customer purchase history and a lead-propensity score before a call, and the target source for both is Databricks: gold Delta tables and a served model. RapidCanvas built the agent platform and its single shared Databricks client before the customer's workspace credentials were available, so today the client's SQL Statement Execution API and Model Serving calls run against a local stand-in with precomputed data. Moving to the live workspace changes a base URL and credentials, not the agents themselves.

Agents are built to call Databricks SQL and Model Serving; production needs only new credentials.
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Databricks questions

RapidCanvas works directly inside customers' Databricks workspaces today; there is no Databricks partner listing or formal partnership in place.
No. Ingestion notebooks and jobs are defined in a Databricks Asset Bundle and deployed from the solution repository with the Databricks CLI, reviewed like any other code.
No. Catalogs, schemas and volumes remain the landing zone and the permission boundary; RapidCanvas queries respect the grants already in place.

See How RapidCanvas Works on Databricks

See how RapidCanvas works with Databricks, or book a discovery call to assess fit for your lakehouse.

Book a Discovery Call
RapidCanvas
G2 Fall 2026 awards: Momentum Leader, High Performer, Best Support, and the Users Love Us milestone
G24.9 out of 5
Gartner Peer Insights5.0 out of 5
Certifications: AICPA SOC, ISO 27001, ISO 45001, GDPR, HIPAA

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