Databricks API

Development / API Key Intermediate HTTPS CORS
Varies by plan (check documentation)

Overview

The Databricks REST API lets you programmatically manage clusters, notebooks, jobs, and workspaces on the Databricks platform — a cloud-based analytics and machine learning environment built on Apache Spark. You can automate cluster lifecycle operations, trigger notebook runs, and retrieve job results without using the UI. An API key (personal access token) scoped to your Databricks workspace is required.

💡

Beginner Tip

Databricks is an enterprise big-data platform aimed at data engineers and ML practitioners rather than general beginners. You need an active Databricks workspace (available on AWS, Azure, or GCP), and your API base URL differs per workspace — it is not a single global endpoint.

Available Data

book title and author
ISBN and publisher
cover image URL
page count
publication date
space mission data

Example Response

JSON Response
{
  "title": "The Great Gatsby",
  "authors": [
    "F. Scott Fitzgerald"
  ],
  "publishedDate": "1925-04-10",
  "pageCount": 218,
  "categories": [
    "Fiction"
  ],
  "imageLinks": {
    "thumbnail": "https://books.google.com/..."
  },
  "averageRating": 4
}

Field Reference

cluster_id Unique identifier for a Databricks cluster, used to reference it in start/stop/delete calls.
state Current cluster lifecycle state: PENDING, RUNNING, RESTARTING, RESIZING, TERMINATING, or TERMINATED.
cluster_name Human-readable name assigned to the cluster when it was created.
spark_version The Databricks Runtime version string (e.g., "13.3.x-scala2.12") used by this cluster.
num_workers Number of worker nodes in the cluster, not counting the driver node.
creator_user_name Email address of the user who created the cluster.

Implementation Example

const url = "https://docs.databricks.com/dev-tools/api/latest/";
// Replace headers or query params with the values required by this API.
const response = await fetch(url, {
  headers: {
  "X-API-Key": "YOUR_API_KEY"
  }
});
if (!response.ok) throw new Error(`Request failed: ${response.status}`);
const data = await response.json();
console.log(data);

What Can You Build?

Note: These code examples are AI-generated and unverified. Always refer to the official API documentation for accurate usage.

Common Errors & Troubleshooting

401 Unauthorized Missing or expired personal access token in the Authorization header
Generate a new token under User Settings > Access Tokens in your Databricks UI and pass it as Authorization: Bearer <token>.
403 Forbidden Token lacks permission for the requested resource, e.g., cluster management requires admin rights
Ask your workspace admin to grant the required entitlements or use an admin-level token for cluster operations.
400 Bad Request on cluster create Required fields like spark_version or node_type_id are missing or invalid for your cloud region
Call GET /api/2.0/clusters/spark-versions and GET /api/2.0/clusters/list-node-types first to get valid values for your workspace.

Matrix Score Breakdown

🌐 Reachability 30/30
⚡ Speed 10/20
🔒 Security 15/15
🛠 Developer XP 17/20
✓ Reliability 10/15

Partially tested on Apr 5, 2026

Technical Specifications

Auth API Key
HTTPS REQUIRED
CORS YES
Category Development
Difficulty Intermediate
Verified: 2026-04-07

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