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.
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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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.
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Dimension | Cost/unit |
|---|---|
Databricks Consumption Units | $1.00 |
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Software as a Service (SaaS)
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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 awsmp-onboarding-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.
Updated weekly
By Databricks, Inc.
By Snowflake
By Alteryx
Top
10
In Databases & Analytics Platforms, Data Analytics, ML Solutions
Top
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In Classification-Text, Embeddings
AI generated sentiment from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
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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
Cloud-Native Architecture
Designed from ground up for cloud infrastructure with scalable and flexible data processing capabilities
Multi-Cloud Data Integration
Supports data unification across multiple cloud platforms and geographies with seamless interoperability
Enterprise-Grade Security
Provides robust data governance, access controls, and secure collaboration mechanisms for organizational data
Distributed Computing Framework
Enables near-unlimited computational resources with high concurrency and performance optimization
Advanced Analytics Platform
Supports diverse analytic workloads and includes enterprise-grade AI model capabilities for data processing
Data Workflow Automation
Drag-and-drop interface with 300+ analytic building blocks for creating and automating data workflows
Machine Learning Capabilities
Automated machine learning (AutoML) and feature engineering for high-value data science use cases
Cloud-Native Analytics Platform
Browser-based, cloud-native experience for building and automating data pipelines with reduced technical complexity
AI-Powered Insights Generation
AI capabilities for generating quick insights through dashboards and storytelling across organizational processes
Enterprise Analytics Governance
Scalable platform for sharing and governing analytic workflow processes with enterprise-level management
Validated by AWS Marketplace
FedRAMP
GDPR
HIPAA
ISO/IEC 27001
PCI DSS
SOC 2 Type 2
No security profile
No security profile
Standard contract
No
No
No
Customer reviews
Prachi M.
Solution For Data Management
Reviewed on May 30, 2025
Review provided by G2
What do you like best about the product?
They have user friendly interface and ease to integrate option that gives very effective and user friendly experience to work on databricks to manage and analyze our company huge datasets.
What do you dislike about the product?
I love their customer support because whenever I need and help regarding integration their team help me to fix my issues.
What problems is the product solving and how is that benefiting you?
Performance and infrastructure of Databricks are top notch and hassle free, they have lots of integration that manage our work more effective and without any issues. they provides lots of predefine algo and templates that help us to create analyze the dataset to create a new insights.
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Geral G.
Databricks - Powerful and scalable for data science and business analytics
Reviewed on May 28, 2025
Review provided by G2
What do you like best about the product?
I like it because it stands out for its ability to unify data science, data engineering, and business analytics into a single interface. I also appreciate the seamless integration with collaborative notebooks and the ability to seamlessly with Delta Lake is also a big plus, ensuring reliability and performance when managing large-scale data.
What do you dislike about the product?
Sometimes, the web interface can take a while to load active clusters. Id also like more visual tools to monitor resource usage in real time.
What problems is the product solving and how is that benefiting you?
One of the main challenges we faced was fragmentation between engineering and analytics teams, and Databricks allowed us to centralize all data processing and analysis, reducing development time and improving the quality of our machine learning models. We also eliminated data sites by consolidating multiple sources into a single platform, which reduced the time to insights and the execution time of ETL pipelines, improved collaboration and overall productivity, and improved business decision supported by cleaner data.
Brandon C.
Great Experience with Databricks
Reviewed on May 28, 2025
Review provided by G2
What do you like best about the product?
The Databricks Data Intelligence Platform allows us to have a single source of development capabilities for IT developers and business analysts. This allows for easier implementation of capabilities and consolidation of toolsets across the environment. Users are given the freedom to develop the data products they need in the time frames they need them. It makes implementation and productionalization of these projects much easier to integrate for downstream usage.
What do you dislike about the product?
The one "dislike" I have is that it's difficult to keep up with all of the improvements and enhancements in the platform. We always see new features to implement and want to make sure we're doing the best we can for our end users.
What problems is the product solving and how is that benefiting you?
Databricks is making it extremely easy for us to have a single set of tooling for multiple us cases in the data space. This allows us to be more collaborative across business units and within business units. It also allows us to have standard ways of working that can be implemented through all of the use cases. We see a lot of capabilities that can be leveraged with the platform that make repeatable capabilities easier which allows us to increase speed to market for our data products
Ethan W.
Databricks makes Teamwork Data Super Easy
Reviewed on May 28, 2025
Review provided by G2
What do you like best about the product?
I like Databricks because it helps everyone work together on big data projects in one place. It’s easy to share ideas, do smart computer stuff, and understand lots of information as a team.
What do you dislike about the product?
Sometimes, it’s hard to move our old data into Databricks. If you are not used to it, learning everything can feel tricky at first.
What problems is the product solving and how is that benefiting you?
Databricks brings all our data together, making teamwork easier and helping us make smart decisions faster.
Albert A.
DataBricks great tool for large-scale collaborative analysis
Reviewed on May 27, 2025
Review provided by G2
What do you like best about the product?
I really liked how easy it is to collaborate on shared notebooks, along with the native support for Spark and integration with MLflow. It allows you to work with large volumes of data without worrying about the underlying infrastructure.
What do you dislike about the product?
It could be said that the learning curve might be better for new users or those who have no previous experience with distributed environments.
What problems is the product solving and how is that benefiting you?
Its a good all-in-one solution for those working with big data and machine learning. Its collaborative environment and scalability make it and excellent tool for our daily workflow, making everything easier, especially when sharing models and pipelines across departments.