Sold by: Dataiku
Dataiku makes data and AI projects a team sport, bringing intelligence to all - from AI builders to AI consumers.
Overview
With Dataiku's 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
Throughout the process, Dataiku's expert team and comprehensive learning curriculum support the rollout of the tools and data science practices to help enterprises adopt AI at scale.
Need something different? For other packages and options please contact us at AWS@dataiku.com
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 using Dataiku's Cloud Stacks Accelerator to get up and running quickly or skip installation and maintenance processes with a fully managed service (SaaS) hosted and managed by Dataiku.
Details
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.
Dimension | Description | Cost/12 months |
|---|---|---|
Discover Annual Edition | Up to 5 users, 20+ DB connectors, limited automation, standard support | $80,000.00 |
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
Vendor 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.
Updated weekly
By Dataiku
By Databricks, Inc.
By Alteryx
Top
50
In ML Solutions, Data Analytics, Collaboration & Productivity
Top
10
In Databases & Analytics Platforms, Data Analytics, ML Solutions
AI generated sentiment 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
Data Integration
Supports ingestion and manipulation of diverse data sources including AWS Athena, Redshift, and external platforms
Machine Learning Collaboration
Enables data scientists to automate repetitive tasks and efficiently collaborate using familiar languages and tools
Cloud Platform Compatibility
Natively integrates with AWS services and products for scalable enterprise AI deployment
Visual Data Preparation
Provides comprehensive visual interface for data cleaning, enrichment, and advanced data pipeline construction
Model Development Environment
Supports advanced machine learning model development through integrations with Amazon SageMaker
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
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
Standard contract
No
No
Customer reviews
Research
My daily use Data Platform
Reviewed on Mar 25, 2025
Review provided by G2
What do you like best about the product?
Like their company motto, Dataiku is our "Everyday AI" platform. From data preparation and Exploratory Data Analysis (EDA), to MLOps and AI models, Dataiku has everything we need to streamline our analytic and AI needs.
Integrating our heterogeneous data sources is simple, and allows our staff to find the data they need and enrich it in just a few steps. The team administrating the platform at our organization can focus all their efforts in providing support and onboarding to our new users, and be sure to have the expert and excellent Dataiku support when needed.
Today, around 20% of our organization's staff uses Dataiku at least once a week, to consume reports and dashboards, or to do their own analysis, thus making the decision making process a more efficient and robust one.
Integrating our heterogeneous data sources is simple, and allows our staff to find the data they need and enrich it in just a few steps. The team administrating the platform at our organization can focus all their efforts in providing support and onboarding to our new users, and be sure to have the expert and excellent Dataiku support when needed.
Today, around 20% of our organization's staff uses Dataiku at least once a week, to consume reports and dashboards, or to do their own analysis, thus making the decision making process a more efficient and robust one.
What do you dislike about the product?
For some users, specially those used to doing all their tasks with code, the onboarding can be challenging. They might struggle to find the added value if they don't have a specific use case to start from.
What problems is the product solving and how is that benefiting you?
Dataiku is solving our problem of producing consistent reports and improving our operations with readily available reports.
Leave a comment0 comments
Manufacturing
Dataiku review
Reviewed on Mar 25, 2025
Review provided by G2
What do you like best about the product?
Dataiku is user friendly and easy to learn. You can combine lots of data resources into one simple platform. I frequently use this in data analytics at my company.
What do you dislike about the product?
I would suggest more open training online to help others see the possibilities of using Dataiku.
What problems is the product solving and how is that benefiting you?
It helps me to combine all of my data into one central location
Financial Services
Dataiku for Advanced Analytics
Reviewed on Mar 24, 2025
Review provided by G2
What do you like best about the product?
Dataiku excels at creating a centralized platform for democratizing data for every user to collaborate regardless of their skill level. The platform is suitable for coders and non-coders, developers and business users, etc. Each release contains new Gen AI, machine learning or analytics capabilities and allows you to connect to source systems, build data workflows, interactive visualizations and automate the entire end-to-end life cycle.
What do you dislike about the product?
I think the user documentation can be challenging to sift through, I wish information was collated within one repository instead of many different links.
What problems is the product solving and how is that benefiting you?
Dataiku allows me to build end-to-end solutions leveraging big data at scale.
Consulting
Great platform for practical EDA and ML purposes
Reviewed on Mar 24, 2025
Review provided by G2
What do you like best about the product?
You'd be hard pressed to create a platform with greater ease of use than Dataiku. Moving around the UI while performing data analytics or when showcasing the work performed by the team is seamless / effortless. New features also come out regularly and are constantly improving the platform. Ease of implementing the platform with other tools, such as Snowflake and Power BI, is also much appreciated.
What do you dislike about the product?
Projects can get unruly once they become large enough. This can be alleviated by creating many flow zones.
What problems is the product solving and how is that benefiting you?
Forecasting customer demand using data ingesting, prep, and time series analysis has been super valuable.
Lucas M.
A game changing data science platform
Reviewed on Mar 24, 2025
Review provided by G2
What do you like best about the product?
It's flexibility. I can code and I like that I can create recipes that uses code to process my data. However, I enjoy having the ability to just select a visual recipe and quickly apply transformations without writing lines of coding. This keeps my skills fresh and gives me a productivity boost when I need to deliver quickly. I use the platform on a daily basis and it forms part of my core tools to develop my projects. As a big organisation, we have our own internal support to deal with issues. However, I've attended a meet up and a conference in London and met the UK team. It was an amazing experience and they offered me a lot of support showcasing new features and facilitating the contact with the Dataiku user community. Another aspect that I enjoy is the seamlessly integration with our current data systems. Using Dataiku, I can connect with all of our data sources and develop projects that weren't even possible before.
What do you dislike about the product?
My only dislike about it is the cost. Although I think it delivers what it promises, the cost is a huge barrier within my organisation. I would like to have more of our analysts with access to a designer licence. That would empower them by developing new skills. Today, only a few data scientist (including myself) and a couple of analysts have full access to the tool.
What problems is the product solving and how is that benefiting you?
When I joined the company, we didn't have a ETL manager. I used to write my SQL queries and build the connections using Power Query. The process was cumbersome and used to take a lot of hours to make small progress. With Dataiku, I now can create my models, schedule the refreshes, save the data in a centralised repository and just expose it to my data visualisation tools (Power BI). Another issue was having the compute power to process our data. I work in the energy industry and our data is all half-hourly. With Dataiku, I can use spark on EKS and process huge amount of data in just a fraction of the time I used to.