Sold by: Dataiku
Deployed on AWS
Accelerate Enterprise AI with Dataiku on AWS
4.4
Overview
Video
Dataiku 3-Minute Demo
Video
Product video
Dataiku is The Universal AI Platform™, empowering teams to deliver AI and analytics projects faster - all within a secure, collaborative, and governed environment.
- Data Scientists use familiar tools to focus on high-impact work, with automation and streamlined collaboration.
- Business Analysts get faster insights with intuitive data prep and accessible machine learning.
- Data Teams scale projects with built-in governance and transparency.
Built for AWS
- Connect securely to all data sources, including Amazon S3, Amazon Redshift, and Amazon RDS.
- Scale data and ML processing with Dataiku elastic compute powered by Amazon EKS for Python, R, Spark, and more.
- Accelerate AI development with pre-built workflows integrating AWS AI services, such as Amazon SageMaker and Amazon Comprehend.
- Distributed creation of advanced analytics through its visual platform, fostering greater collaboration between technical and non-technical teams.
- Leverage the Dataiku LLM Mesh to connect to Amazon Bedrock for Chat, RAG, and Agentic workflows.
AI at Scale, Supported Every Step
With expert services and a robust learning platform, Dataiku helps organizations of any size adopt AI at scale - quickly and confidently.
Highlights
- Take full advantage of your investment in the AWS platform with Dataiku's unique push down to Amazon's storage and compute.
- Empower more users to clean and enrich data, build advanced data pipelines and machine learning models in a visual interface.
- Accelerate deployment on AWS, leveraging Sagemaker and Bedrock, with a fully managed service (SaaS) hosted and managed by Dataiku.
Details
New
Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Features and programs
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.
Pricing
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/12 months |
|---|---|---|
Please contact us for Pricing | Please contact aws@dataiku.com to get a custom quote through Private Offer | $0.01 |
Vendor refund policy
All fees are non-cancellable and non-refundable except as required by law.
Legal
Vendor terms and conditions
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) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
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.
Resources
Support
Vendor support
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.
Similar products
Accelerate Enterprise AI with Dataiku on AWS
A composable Zero Code AI Platform with Deep Learning & AI capabilities such as Predictive Analytics, Neural Networks, Natural Language Processing & Computer Vision with Data Prep, AI Modeling, xAI (Explainable AI), & AI Execution capabilities for Enterprises.
Professional Services for Dataiku Platform including Implementation of the platform and AI, Data Analytics, Machine learning Use Case Implementation.
Customer reviews
Louis K.
Dataiku Streamlines End-to-End AI at Scale with Intuitive, Collaborative Workflows
Reviewed on Jan 15, 2026
Review provided by G2
What do you like best about the product?
Dataiku streamlines building, training, and deploying AI models at scale, offering end-to-end automation, seamless orchestration of compute resources, and collaborative pipelines that make generative AI projects faster and more reliable. It unifies the entire data workflow from preparation and analysis to model deployment, into a single, collaborative platform that’s surprisingly intuitive for both data scientists and business users.
What do you dislike about the product?
Full capabilities can be overwhelming for new users, and scaling extremely large generative AI models sometimes requires complex customization.
What problems is the product solving and how is that benefiting you?
Dataiku solves the problem of fragmented AI workflows by unifying data preparation, model training, and deployment in a single platform. This benefits me by accelerating generative AI projects, reducing infrastructure complexity, and enabling seamless collaboration across data engineers, scientists, and business teams. It ensures models are production-ready faster while maintaining scalability and reliability.
Samantha L.
Centralized, Organized Data Platform with Powerful AutoML and Integrations
Reviewed on Jan 15, 2026
Review provided by G2
What do you like best about the product?
Dataiku demonstrates a satisfactory environment where data is centralized and organized
The program supports both coders and non coders, allowing them to use data in their different levels
Dataiku has a successful data lifecycle, something that collects, ingest, prepare and even analyze data
The program consists of an inbuilt Auto ML tools that speed u most of the operations
Dataiku has extensible APIs and plugins, all supporting success integrations
The program supports both coders and non coders, allowing them to use data in their different levels
Dataiku has a successful data lifecycle, something that collects, ingest, prepare and even analyze data
The program consists of an inbuilt Auto ML tools that speed u most of the operations
Dataiku has extensible APIs and plugins, all supporting success integrations
What do you dislike about the product?
Dataiku has challenges in cost management and estimating, where small companies fail to secure the app
The app demands extensive computer resources, something that amplifies the infrastructure costs
The app demands extensive computer resources, something that amplifies the infrastructure costs
What problems is the product solving and how is that benefiting you?
Dataiku ensure solid data collaboration, where analysts, engineers and even business players access data in a centralized environment
Most of complex data workflows are significantly supported by this app, ensuring that no manual code needed to conduct a specific task
The presence of machine learning and AI support s the effectiveness of data processing and analysis
The app accommodates both technical and non technical users due to it’s effectiveness and simplicity
Most of complex data workflows are significantly supported by this app, ensuring that no manual code needed to conduct a specific task
The presence of machine learning and AI support s the effectiveness of data processing and analysis
The app accommodates both technical and non technical users due to it’s effectiveness and simplicity
Seerapu N.
A Unified Platform That Bridges Data Experts and Business Teams Seamlessly
Reviewed on Jan 15, 2026
Review provided by G2
What do you like best about the product?
Its greatest strength is enabling true collaboration between data experts and business teams on a single platform. It seamlessly bridges technical work like coding and ML engineering with visual and no-code interfaces. This breaks down silos, accelerates project delivery and ensures AI solutions are built with crucial business context, making them more impactful and sustainable.
What do you dislike about the product?
For smaller teams or simpler projects, Dataiku will be premium. The platform's extensive features come with inherent complexity, which can lead to a steeper learning curve. Its pricing model is often seen as enterprise-focused, potentially making it less accessible for startups or individual users who don't need its full collaborative scale.
What problems is the product solving and how is that benefiting you?
Dataiku solves the critical challenges of fragmented data science workflows. It provides a unified, collaborative platform that connects data preparation, experimentation and deployment into one governed environment. This directly benefits us by drastically reducing project lead times, improving model governance and reproducibility and enabling both technical and business users to contribute effectively to data-driven outcomes.
Kajal K.
End-to-End Data Science Platform That Makes Collaboration Easy
Reviewed on Jan 15, 2026
Review provided by G2
What do you like best about the product?
What I like best about Dataiku is its end-to-end data science and machine learning platform that brings data preparation, analysis, model building, and deployment into a single environment. The visual workflows combined with code-based options make it accessible for both technical and non-technical users. It also supports strong collaboration between data scientists, analysts, and business teams, which helps speed up model development and improve decision-making.
What do you dislike about the product?
While Dataiku is a powerful platform, it can feel complex for first-time users because of its extensive feature set. The initial setup and learning curve may take time, especially for non-technical users. In some cases, performance can slow down when handling very large datasets, and the pricing structure may not be ideal for smaller teams or limited use cases.
What problems is the product solving and how is that benefiting you?
It's solves the challenge of managing the entire data science and machine learning lifecycle in one platform. It brings together data preparation, analysis, model development, deployment, and monitoring, reducing the need for multiple disconnected tools. This benefits me by improving collaboration between teams, speeding up model development, and making it easier to turn data into actionable insights while maintaining consistency and governance across projects.
Christopher M.
Effortless Data Collaboration with Robust Features
Reviewed on Jan 14, 2026
Review provided by G2
What do you like best about the product?
I like that Dataiku lets me handle data projects and build machine learning models by pulling in data from different sources, cleaning and organizing it, and experimenting with models all in one place. The combination of a visual interface with coding options makes it accessible for both technical and non-technical team members, smoothing out data project management. I love how it reduces repetitive tasks, decreases mistakes, and keeps complex projects organized and running smoothly. It's great that everyone on the team can contribute, no matter their technical skills, making data work easier and less stressful.
What do you dislike about the product?
One thing I’ve noticed about Dataiku is that it can feel a bit overwhelming at first because there are so many features and options. Working with really large datasets or complex workflows can sometimes be a little slow. I also think it could be a bit easier for new users to get started. Overall, it’s a great tool, but a little more guidance and smoother performance would make it even better.
What problems is the product solving and how is that benefiting you?
I use Dataiku to streamline data projects by integrating data sources, cleaning data, and building models in one platform. It allows team collaboration regardless of technical skills, saves time on repetitive tasks, reduces mistakes, and keeps complex projects organized.