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.
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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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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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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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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
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 Service Integration
Secure connectivity to Amazon S3, Amazon Redshift, and Amazon RDS with push-down computation capabilities
Elastic Compute Scaling
Distributed processing powered by Amazon EKS supporting Python, R, Spark, and other frameworks for data and ML workloads
Pre-built AI Workflows
Integration with AWS AI services including Amazon SageMaker and Amazon Comprehend for accelerated AI development
Large Language Model Integration
LLM Mesh connectivity to Amazon Bedrock enabling Chat, RAG, and Agentic workflow capabilities
Visual Development 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
No
No
Customer reviews
Preetam J.
Robust Data Processing with High Costs and Learning Curve
Reviewed on Apr 26, 2026
Review provided by G2
What do you like best about the product?
What I like the most about Databricks is the performance. When handling a large amount of datasets, it's time-consuming and requires a lot of effort to clean and use the data, but Databricks allows me to do all of that on a single platform. I appreciate that I can have all the tools for processing, storage, and analysis in one place. The notebook feature is also very good, providing a nice experience for writing code, creating pipelines, and more.
What do you dislike about the product?
Things I want to be improved in Databricks is the cost. Like, it's really expensive to be used when we are small scale businesses. I would like the cost to be decreased. There's also a lot of configuration and setup, which makes it hard for junior level users to just start and work with it. It needs more learning modules to help start with the platform. Initial setup wasn't easy, needing certification on data exposure and it was tough because engineers couldn't reset the database properly.
What problems is the product solving and how is that benefiting you?
I use Databricks for large-scale data and analytics, making it easier to handle and process large datasets. It helps analyze data faster, enables efficient data cleaning and transformation, and provides all tools in a single platform for processing, storage, and analysis.
4 Dhiraj B.
Fast, Reliable Lakehouse That Unifies Data Processing and SQL
Reviewed on Apr 25, 2026
Review provided by G2
What do you like best about the product?
Data processing and SQL queries are fast and reliable, and the lakehouse platform really helps unify our work.
What do you dislike about the product?
There’s a steep learning curve that demands advanced coding skills and solid Spark expertise, which can make it feel like overkill for teams that only need straightforward SQL reporting.
What problems is the product solving and how is that benefiting you?
We’ve improved our data team’s productivity by removing the need for manual infrastructure management.
mohammad Gufran j.
Unified Analytics Powerhouse with Minor Hiccups
Reviewed on Apr 25, 2026
Review provided by G2
What do you like best about the product?
I like most about Databricks is that it brings data engineering, analytics, and AI workflow into one shared platform, which makes collaboration much easier. It's valuable for working with a large dataset and notebooks, and it helps set up suitable pipelines without the hassle of managing too many separate tools.
What do you dislike about the product?
Cost visibility and resource users can be hard to track, especially as more teams cluster and jobs start using the platform. I also like to sync up permission management. Clear troubleshooting for a job failure and a smoother experience around the workspace governance and configuration. CDC lake flow is always stuck for a last table and not giving a clear picture till now. Serverless logs are sometimes very difficult to track, making it hard to understand the reason for job failures.
What problems is the product solving and how is that benefiting you?
I find Databricks solves handling large-scale data processing and analytics by unifying data engineering, analytics, and AI workflow into one platform. It simplifies collaboration on notebooks and automation workflows, enabling faster work with big datasets using Spark.
Staffing and Recruiting
Seamless, Scalable Unified Platform for Data, Analytics, and ML
Reviewed on Apr 25, 2026
Review provided by G2
What do you like best about the product?
Its unified platform for data engineering, analytics, and machine learning makes workflows seamless and scalable.
What do you dislike about the product?
It can be expensive and has a bit of a learning curve for new users.
What problems is the product solving and how is that benefiting you?
It simplifies big data processing and analytics in one platform, helping me save time and scale workflows efficiently.
Arkesh K.
All-In-One Platform That Revolutionizes Workflows
Reviewed on Apr 25, 2026
Review provided by G2
What do you like best about the product?
I love that Databricks combines data engineering, SQL analytics, and machine learning in a collaborative platform. My team and I can clean data, run SQL, and build models all in one place without losing our tasks.
What do you dislike about the product?
The price can get scary fast, and sometimes the cluster startup delay makes me feel like I am waiting for a coffee machine that's still warming up.
What problems is the product solving and how is that benefiting you?
I use Databricks to run SQL, clean data, and build models all in one place, eliminating the need for multiple tools while handling huge data efficiently.