Sold by: Databricks, Inc.
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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.
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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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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.
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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
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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
Collaborative Development Environment
Native collaboration capabilities enabling data teams to collaborate across entire data and AI workflow
Open Source Foundation
Built on open source data projects and open standards to maximize flexibility and interoperability with existing data ecosystems
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 and Amazon Comprehend for accelerated AI development.
Large Language Model Connectivity
LLM Mesh capability enabling connections to Amazon Bedrock for Chat, Retrieval-Augmented Generation (RAG), and Agentic workflows.
Visual Analytics and ML Interface
Low-code visual platform for data preparation, pipeline creation, and machine learning model development accessible to both technical and non-technical users.
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
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No
Customer reviews
Anonymous
Empowers Data Pipeline Creation with Robust Community Support
Reviewed on Aug 12, 2026
Review provided by G2
What do you like best about the product?
I like the community. The people that use Databricks are pretty cool people, and I also like how they are a champion for the open source. Having a nice community of technologists to lean on and talk to opens my eyes to the possibilities on the platform. I love being able to do things for free slash cheap, and I also like being able to bring my own tooling and libraries to my projects. Exploring different tooling and libraries that people tell me about is great, and the fact that I can just pull anything I really want from GitHub so simply on Databricks is a huge value add because I can go on to any project and make some magic happen.
What do you dislike about the product?
I think the developer experience in Databricks could be improved. You kind of have to choose between developing in the UI or developing locally, and it's a little bit clunky in my opinion. There are pros and cons to both, so I'd like to see those differences between local development and UI development removed. Also, the initial setup was pretty tough, which wasn't entirely Databricks' fault, but dealing with the high-level security and firewall software of our client added challenges. The Databricks team was helpful in overcoming these hurdles, though.
What problems is the product solving and how is that benefiting you?
I use Databricks to create ETL pipelines, helping my company solve net revenue calculation issues by integrating data from source systems to dashboards. It aids informed decision-making for stakeholders.
Niyonshuti Y.
Revolutionized Data Management with Outstanding Collaboration
Reviewed on Aug 11, 2026
Review provided by G2
What do you like best about the product?
I love using Databricks for bringing all our data together and making sure everything is more organized without isolated areas. The collaborative notebooks are fantastic because they allow me to work on code simultaneously with colleagues, which greatly speeds up the workflow. I also appreciate the Spark integration as it removes the hassle of manually configuring clusters. Databricks saves a lot of time due to the speed at which it processes data. The fact that it's cloud-based made the initial setup easy, which is another plus.
What do you dislike about the product?
Being a bit demanding, I would like them to improve the learning curve, because for someone just starting out it can be a little overwhelming due to the large number of configuration options, permissions, and governance settings.
What problems is the product solving and how is that benefiting you?
Databricks organizes our data, eliminating isolated areas for team collaboration. I love the collaborative notebooks and Spark integration for speedy workflows. It saves us time with quick data processing.
Sarath A.
Easy to Learn and Execute for Anyone
Reviewed on Aug 10, 2026
Review provided by G2
What do you like best about the product?
Anyone can adapt and learn and execute it!
What do you dislike about the product?
There are frequent changing naming convention
What problems is the product solving and how is that benefiting you?
AI automation and agentic releated problems
Anonymous
Comprehensive AI Platform with Unified Governance
Reviewed on Aug 06, 2026
Review provided by G2
What do you like best about the product?
I use Databricks as the backbone for all my data and AI work. I love that everything is in a single place and all connects, which allows me to manage everything from raw data digestion to deploying AI products. Unity Catalog provides a single governance source of truth with permissions throughout the platform, which is incredibly useful. Genie Spaces offer an interface in natural language for non-technical stakeholders, saving me time as I don't need to create additional Tableau reports. I can ship everything as code rather than clicking through notebooks manually, which lets me scale much faster. Databricks is a comprehensive platform and is ahead of the curve when it comes to artificial intelligence.
What do you dislike about the product?
The biggest issue I have is that I'm not applied for admin so I don't have visibility into a lot of my costs or access to control more things in the platform. I also wish there was a way in Genie code to make it more clear which aspects are within my control and which are not, and to have an integrated system to notify my platform admin when there are issues.
What problems is the product solving and how is that benefiting you?
I use Databricks as the backbone for all my data and AI work. It's an all-in-one platform, eliminating the need for handoffs between different tools. Unity Catalog gives me a single governance source, ensuring consistency and saving my time.
Jonathan B.
Amazing Platform for Running AI at Massive Scale
Reviewed on Aug 06, 2026
Review provided by G2
What do you like best about the product?
Amazing platform to run AI on a massive scale without complexity
What do you dislike about the product?
The pricing can be challenging if you don't have enough knowledge
What problems is the product solving and how is that benefiting you?
It’s one of the best ways to run AI and ETL on large amounts of data. Databricks also comes with industry-ready features that make it easier to work at scale.