Sold by: Dataiku
Deployed on AWS
Accelerate Enterprise AI with Dataiku on AWS
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Overview
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Dataiku 3-Minute Demo
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Product video
Dataiku is the Platform for AI Success, the enterprise orchestration layer for building, deploying, and governing AI. In a single environment, teams design and operate analytics, machine learning, and AI agents with the transparency, collaboration, and control enterprises require.
- 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.
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Dimension | Description | Cost/12 months |
|---|---|---|
Dataiku | Contact us for pricing | $1.00 |
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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.
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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.
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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.
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
Self-Service Infrastructure Access
One-click, governed access to data, tools, and compute resources through a self-service portal with support for open-source tools including Jupyter, RStudio, SAS, Anaconda, MATLAB, and distributed compute frameworks like Spark, Ray, Dask, and MPI.
Centralized Knowledge Management
Central hub for AI operations and knowledge across the enterprise enabling reproducibility, reusability, and cross-functional collaboration with audit-ready platform capabilities.
Integrated MLOps Workflows
End-to-end model development, deployment, and monitoring capabilities within a unified platform with support for preferred tools and languages, including seamless integration with Amazon SageMaker.
Multi-Cloud and Hybrid Deployment
Support for deployment across public cloud, hybrid, and multi-cloud environments through Domino Nexus, enabling workload execution across any compute cluster in any cloud, region, or on-premises infrastructure.
Model Governance and Compliance
Turnkey model governance, monitoring, and remediation with robust controls for compliance, reproducibility tracking, and audit-ready processes designed for regulatory requirements including GxP processes.
Standard contract
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Customer reviews
Marco J.
Dataiku: No-Code ETL Powerhouse — Collaborative, Visual, and Python/SQL Friendly
Reviewed on Jun 29, 2026
Review provided by G2
What do you like best about the product?
What I like the most about Dataiku is that it is mostly a no-code platform, and allows technical, and non-technical users to collaborate in an easy way. It is extremely easy to share workbooks between coworkers, easy to set-up (using the web version with any browser - Edge, Chrome, etc.).
The visual recipes make it easy to understand the flow of the pipeline, while also having the flexibility of adding Python or SQL when necessary. For data preparation, automation, and building repeatable workflows, I can say it's the best ETL platform I have used. We use Alteryx in our company, but we are starting to implement our workflows and apps inside Dataiku instead of Alteryx.
The visual recipes make it easy to understand the flow of the pipeline, while also having the flexibility of adding Python or SQL when necessary. For data preparation, automation, and building repeatable workflows, I can say it's the best ETL platform I have used. We use Alteryx in our company, but we are starting to implement our workflows and apps inside Dataiku instead of Alteryx.
What do you dislike about the product?
The main thing I dislike about Dataiku is that the learning curve can be a little steep at the beginning. There are many features, menus, recipes, and project settings available, so it can feel overwhelming until you understand how everything is organized.
Some tasks that seem simple at first may require learning the Dataiku specific way of doing things, especially around flows, datasets, automation, and deployment. Once you get more familiar with the platform, it becomes much easier to use, but the onboarding phase could be smoother with more user-friendly examples and tutorials.
Some tasks that seem simple at first may require learning the Dataiku specific way of doing things, especially around flows, datasets, automation, and deployment. Once you get more familiar with the platform, it becomes much easier to use, but the onboarding phase could be smoother with more user-friendly examples and tutorials.
What problems is the product solving and how is that benefiting you?
Dataiku helps solve the business problem of automating data workflows that would otherwise require manual work across different tools. This is useful when working with APIs, because we can extract data from external or internal systems, transform it, and schedule the process to run automatically.
In the airline industry, having a platform with schedulers is extremely necessary. Many processes depend on updated data, fixed execution times, and reliable automation. Dataiku makes it easier to organize these workflows in one place, reduce manual steps, and monitor the process when something fails.
In the airline industry, having a platform with schedulers is extremely necessary. Many processes depend on updated data, fixed execution times, and reliable automation. Dataiku makes it easier to organize these workflows in one place, reduce manual steps, and monitor the process when something fails.
Gabriel A.
Fast Connections and Smooth Datasource Migrations
Reviewed on Jun 25, 2026
Review provided by G2
What do you like best about the product?
Fast connection and migration of datasources
What do you dislike about the product?
complicated to lear recipes for a person without coding experience
What problems is the product solving and how is that benefiting you?
is fast to build ML models
Meghu D.
Great for Automating Data Workflows, Looking Forward to Gen AI Integration
Reviewed on Jun 25, 2026
Review provided by G2
What do you like best about the product?
As a data analyst, it makes it easier to automate repetitive data processes and workflows. I also like the visual recipes/workflows. But I am looking forward to all the upcoming features as mentioned in the enablement session.
What do you dislike about the product?
A couple of downsides I’ve noticed with Dataiku are the lack of Gen AI integration. I understand it will be added soon, and I’m looking forward to that, but it’s still a gap for now.
What problems is the product solving and how is that benefiting you?
As someone who works at a bank, a lot of my analysis involves financial data, especially in fraud management. Dataiku helps me work through and analyze fraud-related data, including calculating the impact and benefits of our data science models.
Airlines/Aviation
Visually Appealing Low-Code Platform with Easy Cross-Team Collaboration
Reviewed on Jun 25, 2026
Review provided by G2
What do you like best about the product?
low-code option that is visually appealing that has easy collaboration between various teams of different technical levels
What do you dislike about the product?
it takes a while to get used to the UI and find due to some auto documentation can be misleading
What problems is the product solving and how is that benefiting you?
Dataiku was a possible solution for our analytics migration out of Alteryx
Airlines/Aviation
Intuitive and Effective with Some Challenge in Speed
Reviewed on Jun 25, 2026
Review provided by G2
What do you like best about the product?
I like how intuitive Dataiku is, how easy it is to learn to use, and the fluidity of the software. It makes pipelines much more understandable, facilitating their creation and maintenance. I also like that the changes I make mostly propagate throughout the flow; for example, if I change the name of a table, the recipe that uses it updates automatically. Additionally, if I connect a table somewhere else in the flow, the flow adjusts automatically to maintain a certain order.
What do you dislike about the product?
I think the speed. Many times I have to wait a long time for a simple recipe to even start executing.
What problems is the product solving and how is that benefiting you?
Dataiku makes it easy to create and maintain pipelines, making them more understandable. It is intuitive and allows automatic changes in the flow, which improves organization.