Comparison · Data platforms
Curiosity and Databricks
A lakehouse, or the records around it
Curiosity is a finished context layer; Databricks is a data platform to build agents on.
Your data · your environment
Who each tool is for
Different problems, honestly stated
Curiosity
For industrial and regulated teams whose knowledge sits in engineering systems and structured records, where the answer depends on how those records connect, and where the deployment has to run on their own infrastructure.
Databricks
A data and AI platform built on the lakehouse, with tools to build agents and apps on it, such as Agent Bricks and Databricks Apps. It runs in the customer’s cloud account and suits data and engineering teams.
How Curiosity compares
Where the boundary falls
If your data team already runs on Databricks, it is a natural place for analytics. Industrial knowledge also lives outside the lakehouse, in tickets, documents and engineering systems, with permissions of their own.
Records and documents, not only tables
Industrial knowledge lives in tickets, documents, email and engineering systems as much as in the warehouse. Curiosity connects them where they are.
Permissions from the source
Access is synced from each source system, down to the record, rather than modeled again in a second set of grants.
Tools for the people who do the work
Studio builds apps and agents for engineers and support teams, on top of the graph, without a data team in the loop for each one.
Side by side
Feature comparison
The same five questions, answered for both.
Deployment
Cloud or self-hosted, ready to use
Managed, in your cloud account
Data model
Managed context layer and knowledge graph
Lakehouse tables and files
Industrial fit
Built for industrial and enterprise teams
Data and engineering teams
Data reach
70+ systems connected, and yours through a connector you write
What is ingested into the lakehouse
Residency
EU hosted, or entirely your own infrastructure
Your cloud region
Customization
What your team can change
Your own code, interface, data model and configuration. Databricks as its own documentation described it in October 2026. Where it says Not available, the vendor documents no such capability.
Your own code
C# endpoints, AI tools and tasks, compiled in Studio
Python, SQL, Scala and R notebooks and jobs
Your own interface
Your own front end in C#, deployed from git
Databricks Apps in Streamlit, Dash, React, Node.js
Data model
Typed node and edge schemas you define
Unity Catalog tables, views and schemas
Configuration as code
Every change committed to git, pushed to your remote
Declarative Automation Bundles in YAML, CI/CD
APIs and SDKs
REST API, C# and Python library, connector SDK
REST API, SDKs and CLI
AI integration
What AI can build and reach
Whether AI can build on it, who reviews the result, and which models it runs. Databricks as its own documentation described it in October 2026.
AI that builds
Sudo drafts endpoints, tools, schemas and screens
Genie Code agent builds notebooks, pipelines, dashboards
Review before it applies
Every change a diff a person approves, in a sandbox
Asks approval before running code or editing
Model choice
Any major provider, or an OpenAI compatible endpoint
OpenAI, Anthropic, Google, Meta, others, custom models
Models on your servers
Open weights on your servers, or air gapped
Open weights served in Databricks cloud only
Assistant permissions
Built in tools search as the user, per record
Genie Code and agents act as the user
Agent protocols
MCP server and an OpenAI compatible API
Managed MCP servers, MCP client, OpenAI compatible APIs
At Airbus, we developed the next generation of customer support AI assistance tools with Curiosity, enhancing our technical support’s ability to access and navigate vast data from multiple sources, including millions of documents.
Services Innovation Team
Airline Services at Airbus
Data platforms
Other comparisons in this group
Palantir Foundry and AIP
Curiosity gives you a focused context layer; Foundry and AIP are a full operating system.
CompareSnowflake
Curiosity connects records where they live; Snowflake runs agents over the data in its cloud.
CompareDataiku
Curiosity is a context layer teams build on; Dataiku is a platform for data science and AI projects.
CompareYour data. Your infrastructure.