- 4 ratings
- 4.0
- Monthly users
- 4.3M
- Pricing
- Pay-per-Use / Enterprise
- Platform
- Web App / CLI Tool
- Best for
- Software Developers / Scientists
Overview
Databricks is a data and AI platform to build and run apps, agents and AI on your own data. It combines a lakehouse for data warehousing, Lakeflow for batch and streaming ETL pipelines, Lakebase (serverless Postgres integrated with the lakehouse), Agent Bricks to build production AI agents grounded in your data, AI/BI with Genie for natural-language dashb...
Bring AI to your data. Bring AI to the world.
Key Features
Visual analytics
Share visualizations with stakeholders via links, embeds, or scheduled email reports. Databricks plugs into Plugin/Integ
Device-agnostic access
Multi-platform support ensures everyone can use Databricks regardless of their device preference. Databricks serves two
Developer-friendly API
Rate limits and authentication are clearly documented for smooth implementation.
Client libraries available
5 SDKs (e.g., Python, JVM (Java/Kotlin/Scala), and .NET (C#)) help dev teams launch prototypes quickly.
Try before you commit
Live demos and sandboxes simplify evaluation across stakeholders.
Support & service excellence
Databricks unifies tickets, context, and communication so agents resolve faster. Databricks can help customer-facing tea
Video Showcase
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About Databricks
“Bring AI to your data. Bring AI to the world.”
Databricks Snapshot
Key facts we track so you can judge fit before visiting the provider.
- Primary category
- Data Analytics
- Best fit
- Software Developers, Scientists, Business Executives
- Platforms
- Web App, CLI Tool, API +1 more
- Pricing signal
- Pay-per-Use, Enterprise
- Provider context
- Databricks - US
- Known integrations
- Plugin/Integration
- Developer access
- API documentation, Python, JVM (Java/Kotlin/Scala), .NET (C#) +2 more
- Data handling
- Global hosting, Privacy policy linked
Before you choose Databricks
- Confirm Databricks's current limits, renewal terms, and seat pricing on the official site.
- Review privacy, retention, and data-processing terms before using sensitive data.
- Test the integrations or API path against one real workflow before rollout.
- Make sure the supported platform matches where your team actually works.
Listing data is compiled from structured provider information, public signals, submissions, and periodic checks where available. Treat this page as a shortlist aid, then verify pricing, compliance, and product limits with the provider before making a business-critical decision.
How Databricks Works
Understanding the core functionality and approach of Databricks.
Databricks automates the path from data ingestion to insight delivery. Teams spend less time wrangling spreadsheets and more time acting on findings. Scheduled reports and alerts keep stakeholders informed without manual effort.
Key Features
Explore what makes Databricks stand out.
Visual analytics
Share visualizations with stakeholders via links, embeds, or scheduled email reports. Databricks plugs into Plugin/Integration so data stays in sync.
Device-agnostic access
Multi-platform support ensures everyone can use Databricks regardless of their device preference. Databricks serves two audiences: Web App, CLI Tool, and API apps for daily use, plus Python, JVM (Java/Kotlin/Scala), and .NET (C#) SDKs for custom builds.
Developer-friendly API
Rate limits and authentication are clearly documented for smooth implementation.
Client libraries available
5 SDKs (e.g., Python, JVM (Java/Kotlin/Scala), and .NET (C#)) help dev teams launch prototypes quickly.
Try before you commit
Live demos and sandboxes simplify evaluation across stakeholders.
Support & service excellence
Databricks unifies tickets, context, and communication so agents resolve faster. Databricks can help customer-facing teams if its AI outputs stay grounded in approved support material.
Use Cases
Discover how different audiences leverage Databricks.
Distributed team workflows
Cross-platform sync ensures work started on one device continues seamlessly on another.
Accelerate development
With SDKs and webhooks, engineers connect Databricks to deployments, CI/CD, and monitoring pipelines.
FAQ about Databricks
What is Databricks and what does it do?
How much does Databricks cost?
Is Databricks secure and compliant with data privacy regulations?
What platforms does Databricks support?
How can I try Databricks before purchasing?
What file formats does Databricks support?
Who develops and maintains Databricks?
How do I get access to Databricks?
How is usage measured and billed in Databricks?
What deployment options does Databricks offer?
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Compare Similar Tools
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Keep Databricks's listing accurate
Providers can update product facts, pricing context, screenshots, and launch notes. Paid placements are labeled separately and do not replace editorial or data-quality review.
How to Evaluate Databricks
Compare Databricks with Snowflake, Google BigQuery, Amazon Redshift and other alternatives before you decide. The goal is not to pick the most popular product; it is to find the tool that fits your actual workflow, risk level, and budget.
- Step 1Run the demo with one real software developers task, not a sample prompt.
- Step 2Model the full monthly cost at your expected usage, including seats, limits, and overages.
- Step 3Verify the integration path with your existing stack before you commit.
- Step 4Review privacy, retention, and compliance terms before using sensitive data.
Use the video walkthrough to check whether the interface matches the claims. For developer teams, inspect the Python SDK and JVM (Java/Kotlin/Scala), .NET (C#), R/MATLAB, Other support. Review the API documentation for auth, rate limits, errors, and export behavior. For broader context, browse more data analytics tools for software developers, or compare this page against the category hub. New to AI tool evaluation? Start with AI Tool Navigator.
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