Sold by: Dataiku
Deployed on AWS
AWS Free Tier
Accelerate Enterprise AI with Dataiku on AWS
4.4
Overview
This trial version of Dataiku allows you to deploy into your AWS environment for prototyping, testing and evaluating the full extent of Dataiku capabilities.
Dataiku is the Platform for AI Success, the enterprise orchestration layer for building, deploying, and governing AI.
- 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.
With Dataiku visual, end-to-end collaborative AI platform: - Data Scientists spend more time on high-impact AI projects, leveraging the languages and tools they already know, automating repetitive tasks and efficiently collaborating with stakeholders. - Business Analysts generate deeper intelligence, faster, thanks to comprehensive data access, smart data preparation and accessible machine learning. - Data Teams can deliver more projects and more value from analytics and AI all with built in transparency and governance. Dataiku and AWS innovate together to enable organizations of any size to deliver enterprise AI in a highly scalable environment. - Dataiku natively integrates with AWS Services and products to enable organizations of any size to deliver enterprise AI at scale. - Dataiku enables users to ingest and manipulate a wide variety of data including Athena, Redshift and more, from the AWS ecosystem and beyond. - Dataiku empowers analytic teams to extend data science collaboration through integrations with Amazon Sagemaker Get started today with Dataiku on AWS!
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 create 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
Sold by
Categories
Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
OtherLinux 9
Deployed on AWS
New
Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Features and programs
Buyer guide
Gain valuable insights from real users who purchased this product, powered by PeerSpot.
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 and entitlements for this product are managed through an external billing relationship between you and the vendor. You activate the product by supplying a license purchased outside of AWS Marketplace, while AWS provides the infrastructure required to launch the product. AWS Subscriptions have no end date and may be canceled any time. However, the cancellation won't affect the status of the external license.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Vendor refund policy
Refunds are not provided, but one can cancel at any time.
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
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
Please read at https://doc.dataiku.com/dss/latest/release_notes/index.html
Additional details
Usage instructions
Browse to http(s)://INSTANCE_PUBLIC_ADDRESS/
You might need to wait few minutes that the instance starts and initializes.
You will have a first authentication to prove that you're the owner of the instance (with a basic access authentication):
- login = instance id
- password = empty
Then, you will have access to Dataiku DSS visual interface. Note that only Chrome and Firefox are supported.
Administrative (command-line) access can be obtained through ssh centos@INSTANCE_PUBLIC_ADDRESS. A standard installation of Dataiku DSS runs under linux user account "dataiku".
For additional information, or any issue, please see our resources and Q & A pages.
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
Investics DARTS (Data Aggregation Remediation Transformation Service) sample trial data set. DARTS provides automated data delivery services for institutional investors' cloud and non-cloud systems and platforms. This sample trial data set provides a limited set of pre-determined portfolio holdings and historical scenario statistics.
Professional Services for Dataiku Platform including Implementation of the platform and AI, Data Analytics, Machine learning Use Case Implementation.
Customer reviews
dnyaneshwar g.
Amazing Data Ingestion, Analysis, and Interactive Dashboards
Reviewed on Aug 29, 2026
Review provided by G2
What do you like best about the product?
The data ingestion, analysis, and interactive dashboard for visualising the data and presenting it to stakeholders are amazing. The value for money is great, so many data analysis capabilities made Dataiku a perfect solution fit for our problem.
What do you dislike about the product?
I tried integrating the Dataiku APIs into my Python project. It works flawlessly, but it still needs some improvements, and it isn’t that flexible.
What problems is the product solving and how is that benefiting you?
For my organization, Dataiku has helped us analyze well log data, and our decision-making has become much quicker. Reservoir pressure data analysis also helps onsite engineers make faster decisions.
INDRAYUDH B.
Straightforward Visual ML Workflows with Flexible Python and SQL Options
Reviewed on Aug 28, 2026
Review provided by G2
What do you like best about the product?
What I like most about Dataiku is how straightforward it makes working with data and putting together machine learning workflows. After using it for a week, I found the visual interface particularly helpful because it let me explore, clean, and transform data without needing to write code at every step. At the same time, the option to switch to Python and SQL when needed adds a lot of flexibility. Overall, it feels like a solid platform that brings data preparation, analysis, and machine learning together in one place.
What do you dislike about the product?
What I like least about Dataiku is that it can feel a bit overwhelming at first. It offers a lot of features and options, so it takes time to get comfortable with the interface and to figure out the workflow that makes the most sense. For beginners, some tasks can also seem more complicated than they need to be. After using it for a week, I still think it has a lot of potential, but I wish the initial learning curve were smoother.
What problems is the product solving and how is that benefiting you?
Dataiku helps simplify the process of preparing, analyzing, and working with data by bringing everything into one platform. Instead of switching between different tools, I can manage data, create workflows, and experiment with machine learning in one place. This saves time and makes the overall data workflow more organized and easier to manage.
samira Y.
Everything in One Platform
Reviewed on Aug 25, 2026
Review provided by G2
What do you like best about the product?
I like the fact that everything is in one platform.
What do you dislike about the product?
Advanced development requires a lot of learning, and there’s quite a bit to pick up before you feel comfortable with it.
What problems is the product solving and how is that benefiting you?
It solved the problem of fragmented data science workflows by bringing data preparation, analytics, machine learning, deployment, and governance together in one place.
Kartik G.
Streamlined Data Transformation with Visual Ease
Reviewed on Aug 20, 2026
Review provided by G2
What do you like best about the product?
I mainly use Dataiku for data preparation, reporting, and automation. I love the visual workflow as it shows how data moves from the source through various transformations and outputs, making it easier to understand and maintain. The prepare and join features are really useful for cleaning and combining data without having to write everything from scratch. I also appreciate being able to use Python for more flexibility. Dataiku significantly reduces my manual data work by allowing me to build a process once and reuse it, making workflows easier to track and troubleshoot. The initial setup was fairly easy, and once familiar with the interface and flow structure, it was straightforward to create datasets, build workflows, and start working with the data.
What do you dislike about the product?
I find some workflows can get a bit complex as the project grows, and troubleshooting errors isn't always straightforward. I also notice that performance can slow down with larger datasets, and it sometimes takes a little time to figure out exactly where an issue is coming from.
What problems is the product solving and how is that benefiting you?
I use Dataiku for data preparation, reporting, and automation. It reduces manual data work by letting me build reusable workflows, making it easy to track and troubleshoot data changes instead of doing everything manually in Excel or Python.
Ravindra N.
Unified, Low-Code Platform That Boosts End-to-End Data & AI Productivity
Reviewed on Jul 18, 2026
Review provided by G2
What do you like best about the product?
What I like most about Dataiku is its ability to bring data preparation, analytics, machine learning, and deployment into a single collaborative platform. It enables both technical and non-technical users to work together, making it easier to build end-to-end data and AI workflows. Visual, low-code interface for building data pipelines and machine learning workflows. Support for Python, SQL, and R, allowing advanced users to customize projects when needed. Strong collaboration features with versioning and project sharing. Seamless integration with databases, cloud platforms, and big data technologies. Built-in tools for model deployment, monitoring, and governance. For me, the most valuable feature is the combination of visual workflows and code-based flexibility. I can quickly prototype data pipelines visually while still using code for advanced transformations or custom machine learning logic. The biggest benefit is improved productivity. Dataiku reduces the time needed to prepare data, develop models, and deploy AI solutions, while enabling better collaboration between data scientists, analysts, and business teams.
What do you dislike about the product?
The biggest drawback is the complexity of large projects. As workflows grow, managing dependencies, pipelines, and multiple collaborators can become challenging without careful project organization. Complex projects with many datasets and workflows can become difficult to organize and navigate. Some advanced capabilities require a solid understanding of data engineering or machine learning concepts.
What problems is the product solving and how is that benefiting you?
Dataiku solves the challenge of managing the entire data and machine learning lifecycle in one place. Instead of relying on separate tools for data preparation, model development, deployment, and monitoring, Dataiku provides a unified platform that enables teams to collaborate more efficiently. Simplifies data preparation and transformation through visual workflows. Centralizes analytics, machine learning, and model deployment in a single platform. Enables collaboration between data scientists, analysts, engineers, and business users. Integrates with cloud platforms, databases, and big data ecosystems. Supports governance, version control, and monitoring for production AI models. In my workflow, Dataiku helps accelerate data analysis and machine learning projects by reducing the effort needed to build pipelines and manage data. Its visual interface allows quick prototyping, while the ability to use Python and SQL provides the flexibility needed for more advanced use cases. The biggest benefit is improved efficiency and collaboration. Dataiku reduces the time required to move from raw data to production-ready insights, enabling teams to deliver analytics and AI solutions faster while maintaining better governance and reproducibility.