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    Databricks Data Intelligence Platform

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    Deployed on AWS
    Free Trial
    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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    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 awsmp-onboarding-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.

    Details

    Delivery method

    Deployed on AWS
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    Buyer guide

    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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    Pricing

    Free trial

    Try this product free according to the free trial terms set by the vendor.

    Databricks Data Intelligence Platform

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    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.

    Usage costs (1)

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    Dimension
    Cost/unit
    Databricks Consumption Units
    $1.00

    Vendor refund policy

    No refunds

    Custom pricing options

    Request a private offer to receive a custom quote.

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    Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .

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    Usage information

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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.

    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 awsmp-onboarding-help@databricks.com 

    For additional training:

    AWS infrastructure support

    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.

    Product comparison

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    Accolades

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    Top
    10
    In Databases & Analytics Platforms, ML Solutions, Data Analytics
    Top
    10
    In ML Solutions
    Top
    10
    In Data Analysis

    Customer reviews

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    Sentiment is AI generated from actual customer reviews on AWS and G2
    Reviews
    Functionality
    Ease of use
    Customer service
    Cost effectiveness
    Positive reviews
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    Overview

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    AI generated from product descriptions
    Lakehouse Architecture
    Built on a lakehouse foundation providing unified data storage and governance across data engineering, analytics, BI, data science, and machine learning workloads
    Open Source Integration
    Constructed on open source data projects and open standards to maximize flexibility and interoperability across the data ecosystem
    Data Intelligence Engine
    Powered by a Data Intelligence Engine that enables organizational access to data and insights across diverse user roles and technical skill levels
    Unified Data Platform
    Consolidates data, analytics, and AI workloads on a single common platform running on Amazon S3, eliminating traditional data silos
    Collaborative Capabilities
    Provides native collaboration features enabling data teams to work together across the 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 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.

    Contract

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    Standard contract
    No
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    No

    Customer reviews

    Ratings and reviews

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    4.6
    828 ratings
    5 star
    4 star
    3 star
    2 star
    1 star
    76%
    22%
    1%
    0%
    1%
    10 AWS reviews
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    818 external reviews
    External reviews are from G2  and PeerSpot .
    Financial Services

    Flexible Spark SQL/PySpark Development with an Excellent AI Assistant

    Reviewed on Jun 12, 2026
    Review provided by G2
    What do you like best about the product?
    I really appreciate the ease and flexibility of development using Spark SQL or PySpark. We use a mix of the two across different team members. The AI assistant is also excellent. It really helps enable users who are not very technical to still get questions answered and search through data.
    What do you dislike about the product?
    The BI side. We build analytics products from the ingestion of raw data to visualizations and we use a different BI tool. I know Databricks is not necessarily a BI tool but if they could compete with a Quicksight/DOMO/Tableau in this area we would use Databricks for everything.
    What problems is the product solving and how is that benefiting you?
    Databricks is our primary data platform tool in terms of all of the data work we do.
    Arturo S.

    Super Easy Setup and Data Source Integration for Quick ROI

    Reviewed on Jun 11, 2026
    Review provided by G2
    What do you like best about the product?
    Setting up and integration into data sources was super easy… allowed for quick ROI
    What do you dislike about the product?
    So far my interactions with the Databricks platform have been positive
    What problems is the product solving and how is that benefiting you?
    Connecting various data sources into a single platform to then consume
    Konjengbam M.

    Powerful Lakehouse for Big Data, Collaboration, and Efficient Pipelines

    Reviewed on Jun 11, 2026
    Review provided by G2
    What do you like best about the product?
    I love this platform for its capability to handle big pool of data efficiently. I love the idea of Data Lakehouse of this platform. The Collaborative work supported by this platform greatly enhances productivity and team work. In our context of using the Databricks SQL query we can easily identify the best match of entrepreneurs needed to avail a specific scheme. This saves both time and increases efficiency. The capacity of this platform to analyze the past performance and trends enable us to map out a highly targeted approach that is really efficient. I love the capability of this platform as it can identify probable stress asset which might be an issue for future investment. This makes us rethink our strategy and approach towards the best and efficient way forward. I feel that the platform have a user friendly interface. I love the integration ability of this platform as it integrates with most of the major platform. This makes this platform more robust and powerful. The onboarding of this platform is also easy as we could easily login with our Google ID. Other than this I love the ability of this platform to create pipeline. The capability of this platform to create agents also ease up tasks. It also enhances capability to handle work load more effectively and efficiently.
    What do you dislike about the product?
    I love most part of this platform but I have to admit that user will need a some training for the user to be more efficient. I feel that having a more technical experience will adapt well with this platform. I also wish that the pricing of this platform was also more moderate. Frankly saying the accuracy of output of this platform depends on how clean the Data is . So there is always a chance of spilling in the unclean data. This will directly impact the result.
    What problems is the product solving and how is that benefiting you?
    Frankly this platform translates into assistance in accurate decision making. The decision made by using this platform directly impacts productivity and averts risk.
    Rohan M.

    Streamlined Collaboration and Predictive Insights with Databricks

    Reviewed on Jun 09, 2026
    Review provided by G2
    What do you like best about the product?
    I appreciate how Databricks helps our different teams to collaborate together. A shared notebook project allows our marketing analysts, supply chain engineer, and data scientist to work together in real-time. The version history within Databricks prevents any confusion about the latest developments. I like that it helped us build predictive models to forecast demand more accurately, and we created visual dashboards that we shared with our leadership team, giving them clear regional insights. Within a few months, we saw measurable lifts in sales and improved profit margins. Databricks streamlined processes that used to take weeks of manual spreadsheets and emails, now happening in days with fresh and reliable data. The cross-departmental data sourcing it provides breaks down silos in our organization, enabling smarter and faster decision-making based on a complete picture rather than fragmented departmental views. The setup was straightforward right on the cloud, avoiding messy offline setups.
    What do you dislike about the product?
    There were delays in obtaining permissions for enterprise security and approval workflows while sharing data.
    What problems is the product solving and how is that benefiting you?
    Databricks enables real-time collaboration across teams, fosters holistic insights by breaking down departmental silos, and speeds up processes that used to take weeks. It helps in building predictive models, sharing clear visual insights, and making smarter decisions with reliable data.
    Siddharth V.

    Seamless Data Visualization and Storage with Databricks

    Reviewed on Jun 07, 2026
    Review provided by G2
    What do you like best about the product?
    I really love that Databricks has a UI that is essentially very simple to understand, and the categorizations of data make it easy to find and manage repositories. It's also very easy to set up jobs right on the fly without writing extensive scripts, which is a really good functionality. The native visualizations on Databricks allow me to uncover a lot of insights and make business-driven decisions. Additionally, the role-based access is very seamless, and the functionality provided by Databricks makes it very valuable. The native notebooks feature is also very, very valuable. Overall, with the amount of functionality it has, using Databricks is a buy.
    What do you dislike about the product?
    Maybe the multi-select cursor functionalities, which I initially had in open source Redash, might be very useful for productivity. It's a minor kind of functionality. Other than that, Databricks is really useful, and not much changes which I would recommend.
    What problems is the product solving and how is that benefiting you?
    I use Databricks for usage analytics, understanding data storage, uncovering insights, visualizing data, and making business-driven decisions.
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