Sold by: Databricks, Inc.
Deployed on AWS
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The Databricks Data Intelligence Platform unlocks the power of data and AI for your entire organization. Enjoy up to $400 in usage credits during your 14-day free trial. Cancel anytime. After your trial ends, you will automatically be enrolled into a Databricks pay-as-you-go plan.
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Overview
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Databricks at AWS re:Invent 2024
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Get started today with up to $400 in usage credits during your 14-day free trial. Trial ends the earlier of when credits are consumed or the 14-day period expires. After your trial ends, you will be automatically enrolled into a Databricks pay-as-you-go plan using the payment method associated with your AWS Marketplace account, paying only for what you use and you can cancel anytime. You can view the full per-product rates for Databricks Units (DBUs) at https://www.databricks.com/product/pricing
The Databricks Data Intelligence Platform allows your entire organization to use data and AI. Its built on a lakehouse to provide an open, unified foundation for all your data and governance. And its powered by a Data Intelligence Engine that speaks the language of your organization so anyone can access the data and insights they need.
The Data Intelligence Platform simplifies your modern data stack by eliminating the data silos that traditionally separate and complicate data engineering, analytics, BI, data science and machine learning. Databricks is built on open source and open standards to maximize flexibility. And the platforms common approach to data management, security and governance helps you operate more efficiently and innovate faster across all analytics use cases.
Reach out to sales@databricks.com to get specialized configurations and pricing for Databricks on AWS Marketplace on a contract basis.
** Technical Support: For help setting up your account, connecting to data, or exploring the platform please reach out to help@databricks.com **
Highlights
- Simple: Databricks provides a simplified data architecture by unifying data, analytics and AI workloads on one common platform running on Amazon S3.
- Open: Built on top of the world's most successful open source data projects, the Lakehouse Platform unifies your data ecosystem with open standards and formats.
- Collaborative: With native collaboration capabilities, the Databricks Lakehouse Platform unifies data teams to collaborate across the entire data and AI workflow.
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Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Free trial
Try this product free according to the free trial terms set by the vendor.
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Cost/unit |
|---|---|
Databricks Consumption Units | $1.00 |
Dimensions summary
This listing bills through a single dimension: Databricks Consumption Units. You pay based on your actual usage, with no upfront commitment. Consumption is measured by compute processing power drawn as you run workloads. The unit rate you consume varies with the type of workload you run, such as data engineering, data warehousing, interactive, or AI processing. Because pricing is usage-based, your cost scales up or down with how much you use. Charges accrue as you consume and are drawn against your Consumption Units.
Top-of-mind questions for buyers
A Databricks Unit is a normalized measure of processing power used for billing. The number consumed reflects the compute resources used and the amount of data processed. Consumption is metered at per-second granularity as you run workloads, so you pay only for what you actually use.
Yes. The unit rate varies by workload type. Data engineering, data warehousing, interactive workloads, and AI or model serving each draw Consumption Units at their own rates. Serverless and classic compute options also consume at different rates. The workload you choose determines how quickly your units are drawn.
Consumption Units are drawn based on compute usage, so charges accrue while workloads run. Pricing covers compute processing only. Storage, networking, and related cloud infrastructure are billed separately and vary by service and region. Non-serverless usage does not include underlying AWS resources such as EC2 instances.
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Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
Resources
Support
Vendor support
Please reach out to sales@databricks.com with any questions or for options on contract or pricing terms.
Technical Support: For help setting up your account, connecting to data, or exploring the platform please reach out to help@databricks.com
For additional training:
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AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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By Databricks, Inc.
By Cloudera
Top
10
In Databases & Analytics Platforms, ML Solutions, Data Analytics
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In ML Solutions
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In Data Analysis
Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
Mixed reviews
Negative reviews
AI generated from product descriptions
Lakehouse Architecture
Unified data foundation built on lakehouse architecture providing open, unified foundation for data and governance with support for open standards and formats
Data Intelligence Engine
Powered by Data Intelligence Engine that enables organization-wide access to data and insights across all users and roles
Multi-Workload Unification
Consolidates data engineering, analytics, business intelligence, data science and machine learning workloads on a single common platform
Open Source Foundation
Built on open source data projects and open standards to maximize flexibility and interoperability across data ecosystem
Collaborative Capabilities
Native collaboration features enabling unified data teams to collaborate across entire data and AI workflow
AWS Data Source Integration
Secure connectivity to Amazon S3, Amazon Redshift, and Amazon RDS with push-down computation capabilities.
Elastic Compute Scaling
Distributed data and machine learning processing powered by Amazon EKS supporting Python, R, Spark, and additional frameworks.
AWS AI Service Integration
Pre-built workflows integrating AWS AI services including Amazon SageMaker, Amazon Comprehend, and Amazon Bedrock for chat, RAG, and agentic workflows.
Visual Analytics and ML Interface
Visual platform enabling creation of advanced analytics, data pipelines, and machine learning models accessible to both technical and non-technical users.
Governance and Transparency Framework
Built-in governance, transparency, and control mechanisms for managing AI projects, deployments, and team collaboration at scale.
Workload Auto-scaling
Intelligently autoscales workloads up and down across hybrid and public cloud environments for optimized cloud infrastructure utilization.
Multi-function Analytics Platform
Provides integrated data warehouse, machine learning, and custom analytics capabilities with unified analytic functions to eliminate data silos.
Shared Data Experience (SDX)
Implements security and governance policies that are set once and applied consistently across all data and workloads, with portability across supported infrastructures.
Data Lifecycle Management
Manages complete data lifecycle functions including ingestion, transformation, querying, optimization, and predictive analytics across multiple cloud environments.
Unified Security and Governance
Ensures all workloads share common security, governance, and metadata with capabilities for data discovery, curation, and self-service access controls.
Standard contract
No
No
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Customer reviews
Richard C.
Impressive ML Implementation and Fast Complex Query Performance
Reviewed on Sep 02, 2026
Review provided by G2
What do you like best about the product?
I like how the machine learning model is implemented, and I’m impressed by the processing speed when running complex queries on massive datasets.
What do you dislike about the product?
At times, schedule delay predictions don’t work reliably in systems that depend directly on data stored in the Lakehouse.
What problems is the product solving and how is that benefiting you?
So far, everything has been going well with Databricks. Processing technical data no longer presents major obstacles, since we can now efficiently handle massive files of design and sensor data.
Raheel S.
Scalable Data Processing with an Intuitive Interface
Reviewed on Sep 02, 2026
Review provided by G2
What do you like best about the product?
I like the data processing and the intuitive interface, and I especially appreciate the scalability. It lets me manage both small and large projects without affecting performance, which is something not all platforms can do.
What do you dislike about the product?
What I didn’t like was the support team. They take a long time to respond, and when they do, their replies are usually generic and don’t include much detail.
What problems is the product solving and how is that benefiting you?
I use it to conduct exploratory project analyses and present the results to senior management so they can adjust the models in real time. This has changed the way I approach projects, and I find that beneficial.
Zakaria I.
Versatile Platform Streamlining Data Tasks
Reviewed on Sep 01, 2026
Review provided by G2
What do you like best about the product?
I use Databricks extensively because it's excellent software that allows me to create and implement machine learning models for optimizing risk assessment, claims management, and fraud detection. I really like its integration with different data sources to consolidate the information we use in decision-making. It helps me process data faster and more efficiently, which is essential given the volume and variety of data I handle. I appreciate how it facilitates collaboration between data teams and addresses data security management challenges with integrated tools ensuring regulatory compliance. I like the interface and its robust data visualization features, which make interpreting the results more accessible to all team members. My favorite aspect is its flexibility, allowing me to work with different programming languages and choose the best approach for each task based on team skills and project requirements. Also, the implementation was straightforward as it was a collaborative process involving several teams within the organization.
What do you dislike about the product?
It's a good tool, I see almost no drawbacks. However, I would suggest improving the documentation and training resources, as this would significantly accelerate the adoption of new features within the team.
What problems is the product solving and how is that benefiting you?
I use Databricks to create and implement machine learning models, optimizing risk assessment, claims management, and fraud detection. It processes data efficiently, enhances collaboration, and manages data security compliance. Its integration with different data sources and user-friendly visualization features also benefit decision-making.
Recommendations to others considering the product:
To enhance the user experience, consider expanding the documentation and training resources. This would facilitate quicker adoption of new features and improve overall team efficiency.
Kiani J.
Centralized Governance and Streamlined Data Operations
Reviewed on Aug 31, 2026
Review provided by G2
What do you like best about the product?
I love how Databricks processes information at scale and orchestrates large data flows effectively. It breaks down barriers caused by data silos, making it a single source of reliable information, which is a huge relief for me. I like that it eliminates a lot of friction when connecting microservices or APIs to large flows of processed information. What I value most is the centralized governance.
What do you dislike about the product?
I find it problematic to configure certain network permissions and connectivity between services. I also believe that cost reductions and better infrastructure management would be beneficial. Honestly, I found the implementation a bit complicated, but it was worth it.
What problems is the product solving and how is that benefiting you?
I use Databricks to process information at scale, eliminating data silos, and streamlining large-scale projects. It breaks down barriers between teams by serving as a single reliable information source and centralizes governance. It reduces friction in connecting microservices and streamlines reviews with other teams.
Henry C.
Intuitive and Powerful: AI Genie Makes SQL Easy for Everyone
Reviewed on Aug 28, 2026
Review provided by G2
What do you like best about the product?
It’s very intuitive. The AI genie feature is also really helpful for non-technical folks when they need to write SQL queries. Excellent value!
What do you dislike about the product?
It is well integrated with multiple platforms. For example, for us, we transform our data from Hubstaff Timer and are able to generate from our different layers, from silver to gold. The charts are very, very performative as well. Great integration as well as performance
What problems is the product solving and how is that benefiting you?
Solving the real-time data as well as metrics for our campaigns, it's able to process on a nightly basis, which is very helpful.