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 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.
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Dimension | Cost/unit |
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Databricks Consumption Units | $1.00 |
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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
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Updated weekly
By Databricks, Inc.
By Cloudera
Top
10
In Databases & Analytics Platforms, ML Solutions, Data Analytics
Top
10
In ML Solutions
Top
10
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
Data Platform Architecture
Unified platform integrating data engineering, analytics, business intelligence, data science, and machine learning on a single architecture
Open Source Foundation
Built on open source data projects with support for open standards and data formats
Lakehouse Infrastructure
Provides a common data management approach using a lakehouse architecture running on Amazon S3
Data Intelligence Engine
Advanced engine capable of interpreting organizational data context and enabling broad data access across teams
Collaborative Workflow
Native collaboration capabilities enabling cross-functional data and AI workflow integration
Data Source Connectivity
Secure connection to multiple AWS data sources including Amazon S3, Amazon Redshift, and Amazon RDS
Elastic Compute Processing
Scalable data and machine learning processing powered by Amazon EKS supporting Python, R, Spark, and multiple programming environments
AI Service Integration
Pre-built workflows integrating with AWS AI services like Amazon SageMaker and Amazon Comprehend
Large Language Model Connectivity
LLM Mesh capability for connecting to Amazon Bedrock to support Chat, Retrieval-Augmented Generation (RAG), and Agentic workflows
Collaborative Analytics Platform
Visual platform enabling distributed creation of advanced analytics with collaboration between technical and non-technical teams
Data Platform Architecture
Enterprise data platform supporting multi-cloud, hybrid cloud, and on-premises data management environments
Security and Governance Framework
Shared Data Experience (SDX) technology providing consistent security and governance policies across data workloads and infrastructures
Multi-Function Analytics
Integrated analytics platform supporting data ingestion, transformation, querying, optimization, and predictive modeling without requiring separate point products
Workload Optimization
Intelligent autoscaling capabilities for dynamically adjusting cloud infrastructure resources based on computational requirements
Data Lifecycle Management
Comprehensive platform supporting data processing across multiple services including Data Warehouse, Machine Learning, and custom analytics environments
Standard contract
No
No
No
Customer reviews
Preetham C.
Finally Databricks Data Intelligence Platform has given us stability with Spark jobs.
Reviewed on Jan 06, 2026
Review provided by G2
What do you like best about the product?
I am glad my leg is not completely dead from having to wait for a query (at least the auto termination feature works and saved me money) History is somewhat useful I rely on it to pull up previous scripts I write because I always seem to forget what I did the day before. I think it helps keep finance off my back by saving them money on the AWS bill. To me, it's simply one central location for managing our big data so I do not have to watch 5 monitors.
What do you dislike about the product?
If I want to find a query that was run over 30 days ago the search function does not even come close to being able to help me and also installing R Packages is a complete nightmare and the error messages are as clear as mud. And when working with large amounts of data the user interface becomes sluggish and trying to scroll through a notebook is like pushing through the mud. It would be nice if it were easier to install/ manage external spark packages.
What problems is the product solving and how is that benefiting you?
We create Machine Learning Models and perform Heavy ETL for the Analytics Department. It does a good job partitioning our data so we can query smaller time frames without having to sit around for hours waiting. It also allows our data team to focus on their actual work rather than constantly fixing broken clusters which is nice.
Sumit S.
Excellent Platform for Scaling LLMs and Managing Multi-Cloud Data
Reviewed on Dec 28, 2025
Review provided by G2
What do you like best about the product?
This platform is excellent for scaling large language models (LLMs) and generative AI applications. It offers a unified location to manage security and access data files across multiple cloud environments.
What do you dislike about the product?
Databricks is designed for handling large data sets, so using it for smaller tasks can feel excessive.
What problems is the product solving and how is that benefiting you?
This tool removes the long wait times marketers often face when they need a data engineer to create even a basic report. It also enables us to develop our own AI models using our internal documents, all while maintaining security and peace of mind.
Aditya V.
Powerful EDA Tool with Interactive Notebooks
Reviewed on Dec 27, 2025
Review provided by G2
What do you like best about the product?
I like its usable interface and the interactive notebooks that support SQL and Python for visualization in one place.
What do you dislike about the product?
For learners it may be difficult for beginners and cost may rise quickly
What problems is the product solving and how is that benefiting you?
I use Databricks Data Intelligence Platform for EDA on large datasets. It processes large sets of data for analysis, and I like its usable interface and interactive notebooks that support SQL and Python for visualization.
Christopher C.
Databricks Data Intelligence Platform actually works and saves money
Reviewed on Dec 21, 2025
Review provided by G2
What do you like best about the product?
The autoscale works well; it also helped us reduce the cost of using cloud resources. I thought that was going to be a problem since this is the first time we used autoscale. The support has been good enough, they normally appear on time for their scheduled hours to assist us in fixing the problems we create. The ability to save the query history in order of how the queries were written is nice as I often forget what I write a few minutes after writing it. When working with coworkers who need access to your code you can send them the permalink (link) to the code which is better than having to explain it. Since it supports both Spark and Presto within one tool I do not have to jump between tools.
What do you dislike about the product?
I hate the way the search function works. I have never found the results from a month ago, and it is annoying. The UI will occasionally lag behind my typing, and if I am in a rush I feel it takes too long. Also it would make much more sense for the tables drawer to remain open when I click on the notebook and instead of closing automatically which is very time consuming as I need to reopen it again. I have had the support team tell me they cannot replicate an issue which is no help at all.
What problems is the product solving and how is that benefiting you?
We are able to process large amounts of data using Databricks without having to build out a large ops team to manage our clusters. We can scale up and down so we only pay for the time we are running jobs in the cloud. I use it to see sales numbers on a daily basis although I am not a data engineer. Databricks allows us to run pipelines with Airflow without all of the things crashing right away. Databricks reduces the amount of admin work involved in building and managing clusters.
Rahul D.
All-in-One Data Platform with Seamless Integration and Top Performance
Reviewed on Dec 18, 2025
Review provided by G2
What do you like best about the product?
I like how Databricks brings data engineering, analytics, and AI into a single platform. The Spark and Delta Lake integration is seamless, performance is excellent, and collaboration through notebooks is very smooth. Its tight integration with Azure services also makes data pipelines, security, and scaling much easier.
What do you dislike about the product?
The main downside is the cost, especially when running large or long-running workloads. Debugging complex Spark jobs can also be challenging at times, and fine-tuning performance often requires a good understanding of Spark internals.
What problems is the product solving and how is that benefiting you?
Databricks solves the challenge of processing and managing large-scale data efficiently by providing a unified platform for data engineering, analytics, and AI. It reduces pipeline complexity, improves performance, and enables faster development and collaboration, helping us deliver reliable data solutions with less operational overhead.