Navigate lakehouse objects clearly
Move through catalogs, schemas, tables, and views, inspect their structure, and read data while keeping the wider investigation in one place.
Connect Databricks analysis to the systems that use it.
Explore catalogs, schemas, tables, and views, run Databricks SQL, and connect lakehouse work to cross-source transformations, project lineage, semantic models, apps, and functions.
- Type
- Lakehouse and analytics
- Explore
- Catalog/database → schema → table or view
- Connect with
- Workspace hostname, HTTP path, optional catalog, port, and supported token or OAuth settings
What WhoDB lets your team do with Databricks
Move from exploring Databricks to building useful workflows, shared tools, and trusted data products—all without losing the context behind the work.
Updated August 25, 2026. Available actions depend on the permissions granted to your connected account.
Run Databricks SQL
Run Databricks SQL from the shared WhoDB project and keep query results connected to the workflows, models, apps, and functions that depend on them.
Build workflows across systems
Combine Databricks data with supported operational databases, warehouses, files, and services through visual transformations with previews and run history.
Put trusted results to work
Trace project impact, attach business meaning through semantic models, and turn approved results into reusable functions or internal apps.
From connected data to a workflow people can trust
Connect the SQL endpoint
Configure the workspace hostname and required HTTP path, then choose the supported token or OAuth settings appropriate for the environment.
Explore before transforming
Use catalog, schema, and table context to validate the data behind a question before it becomes pipeline logic.
Make cross-source logic visible
Build transformations that include Databricks and the operational systems around it, with previews and execution history the team can inspect.
Follow the result downstream
Connect the output to project lineage, models, functions, and applications so consumers can see what it depends on and why it exists.
A Databricks SQL client for the wider data operation
Databricks provides a broad environment for lakehouse engineering, analytics, and AI. WhoDB is most useful when Databricks must sit beside the rest of the operating stack in one understandable project and its outputs must flow into tools people use.
WhoDB brings Databricks exploration and SQL into the same project as your operational systems, so analysis can continue into shared workflows, lineage, models, apps, and functions.
WhoDB is a strong fit for
- Teams connecting lakehouse outputs to operational systems
- Cross-source transformations that include Databricks SQL
- Impact analysis spanning tables, transforms, functions, and apps
- Organizations helping more teams understand and use Databricks data
Databricks integration questions
Straight answers about setup, everyday tasks, and how WhoDB fits into your workflow.
What does WhoDB browse in Databricks?
WhoDB lets teams move through Databricks catalogs, databases, schemas, tables, and read-only views, then inspect schema details and rows in one place.
Can WhoDB run Databricks SQL?
Yes. Connect your Databricks workspace with its hostname and HTTP path, then run SQL from WhoDB alongside the related workflows, lineage, models, and tools.
Which Databricks authentication settings are supported?
Connect with an access token or OAuth. Client credentials and Azure tenant settings are available when required by the chosen authentication method.
Is WhoDB trying to replace the whole Databricks platform?
No. WhoDB complements Databricks by connecting its data to the rest of your stack. It is strongest when teams want shared workflows, lineage, semantic models, apps, and functions across multiple systems.
Explore another source
Give your team one place to explore, understand, and build with data across the systems you already use.
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