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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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 help@databricks.com
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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
No
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Customer reviews
Anonymous
Streamlined Automation with Seamless Workflow Integration
Reviewed on Jul 18, 2026
Review provided by G2
What do you like best about the product?
I use Databricks to manage workflows and automate tasks, which has been really productive for my team over the past two years. It handles visualization tasks and manages different functions smoothly, with a high response time. I prefer Databricks for documentation, automation, data mining, and lead gen analysis, which helps in getting a higher ROI by syncing different tasks within one main parent workflow. Its speed and ease of use, along with no credit-based system, multiple integrations, and easy data extraction and sharing capabilities make it a must-have tool.
What do you dislike about the product?
I think there are not a lot as it is one of the best firm but maybe a better informational content can help in easy education as compared to the onboarding process we had but had to watch multiple videos on YouTube and read articles by the firm after it's launch and we went live with the product.
What problems is the product solving and how is that benefiting you?
I use Databricks for managing workflows and automating tasks, solving visualization issues, syncing tasks into a parent workflow, and integrating with tools. It enhances productivity, offers high response time, and supports data mining and lead gen analysis.
Internet
Unified, Scalable Databricks Platform for Collaborative Data Engineering and ML
Reviewed on Jul 17, 2026
Review provided by G2
What do you like best about the product?
What I like most about Databricks is its unified platform for data engineering, analytics, and machine learning. It makes working with large datasets much easier and allows different teams to collaborate in a single environment. I especially like the notebook-based workspace, its scalability, and its integration with Apache Spark.
What do you dislike about the product?
What I dislike about Databircks is that the platform can come with a learning curve for new users, especially when you’re dealing with advanced configurations and large-scale data pipelines. Managing compute resources and keeping costs under control can also take careful monitoring and ongoing attention.
What problems is the product solving and how is that benefiting you?
It helps solve the challenge of managing, processing, and analyzing large volumes of data across different workflows. It brings data engineering, analytics, and machine learning into a single platform, which reduces the need to switch between multiple tools and makes it easier to keep work consistent from end to end.
Marek K.
Dependable Data Source, Impressive Speed
Reviewed on Jul 17, 2026
Review provided by G2
What do you like best about the product?
I appreciate having a dependable source for figures essential to documentation, like installation records, site performance data, and warranty data that I can query directly rather than relying on outdated spreadsheets. I really like the Genie feature because it allows me to ask questions in plain language and get usable answers without waiting for someone else to process a request. It works quickly and can handle large record sets efficiently, which still impresses me compared to previous methods. The dashboards offer a standing view of frequently cited data, which helps me quickly assess any changes rather than manually re-checking each number. The initial setup of Databricks was quite easy as we didn't encounter any major issues.
What do you dislike about the product?
Data does not always travel between platforms as cleanly as I would expect. Where a table comes across from another system, it is not consistently available to me on this side, so I am left reconciling definitions that ought to match already. It is the one area where I feel the groundwork was laid later than it should have been.
What problems is the product solving and how is that benefiting you?
I find Databricks provides a dependable source for my documentation figures, ensuring accuracy and traceability. I can query data directly, making document revisions faster. With Genie and dashboards, I can verify and track data without waiting on requests, improving my work speed and efficiency.
Danny A.
Streamlined Fraud Detection, But Pricey Continuous Workloads
Reviewed on Jul 15, 2026
Review provided by G2
What do you like best about the product?
I love that the Databricks notebook environment makes it easy for our data scientists and engineers to work in the same space without constantly handling code back and forth between separate tools, which used to slow down every model iteration. The integration with our streaming infrastructure has been genuinely solid, allowing us to pull transactions in continuously without a lot of custom plumbing on our end. I also appreciate that pushing score results back out to our decision engine is just as smooth. The performance and load have held up well during peak shopping periods when transaction volume spikes hard, and the pipeline manages to keep pace without falling behind.
What do you dislike about the product?
What I don't really like is the pricing for running continuous streaming workloads, which adds up fast compared to the batch jobs we used to run since clusters need to stay active rather than spin up on a schedule. Justifying the ongoing cost took some real modeling on our end before finance was fully onboard. The AI assistant built into their platform helps with general coding tasks but doesn't offer anything specific to fraud modeling itself, so any real intelligence in our detection logic still comes entirely from our own data science teamwork, not the platform.
What problems is the product solving and how is that benefiting you?
I use Databricks to move fraud detection scoring to a near real-time pipeline, which significantly reduced our losses by evaluating transactions within seconds instead of hours.
Zeeshan A.
Efficient Data Management with Room for UI Improvements
Reviewed on Jul 15, 2026
Review provided by G2
What do you like best about the product?
I especially like the ability to generate visualizations within the same platform, which saves me a lot of time by not having to constantly export the data to make the information understandable. The real-time collaboration capabilities and processing speed are undoubtedly excellent, and the fact that it can be installed on a laptop and allows me to view the team's progress is superb. The initial setup was surprisingly efficient.
What do you dislike about the product?
I believe that, although I am comfortable using IT tools, the user interface for quick report generation could be improved, making it more intuitive for people who are not used to writing code. In other words, the module should be a little more flexible, allowing dragging and dropping of elements as easily as the visualization tools.
What problems is the product solving and how is that benefiting you?
I use Databricks to manage and extract technical information effortlessly, saving time by generating visualizations without exporting data, and benefiting from real-time collaboration and processing speed.