Best Data Science Software for Amazon Web Services (AWS)
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Compare the Top Data Science Software that integrates with Amazon Web Services (AWS) as of June 2025
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This a list of Data Science software that integrates with Amazon Web Services (AWS). Use the filters on the left to add additional filters for products that have integrations with Amazon Web Services (AWS). View the products that work with Amazon Web Services (AWS) in the table below.
What is Data Science Software for Amazon Web Services (AWS)?
Data science software is a collection of tools and platforms designed to facilitate the analysis, interpretation, and visualization of large datasets, helping data scientists derive insights and build predictive models. These tools support various data science processes, including data cleaning, statistical analysis, machine learning, deep learning, and data visualization. Common features of data science software include data manipulation, algorithm libraries, model training environments, and integration with big data solutions. Data science software is widely used across industries like finance, healthcare, marketing, and technology to improve decision-making, optimize processes, and predict trends. Compare and read user reviews of the best Data Science software for Amazon Web Services (AWS) currently available using the table below. This list is updated regularly.
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Saturn Cloud
Saturn Cloud
Saturn Cloud is an AI/ML platform available on every cloud. Data teams and engineers can build, scale, and deploy their AI/ML applications with any stack. Quickly spin up environments to test new ideas, then easily deploy them into production. Scale fast—from proof-of-concept to production-ready applications. Customers include NVIDIA, CFA Institute, Snowflake, Flatiron School, Nestle, and more. Get started for free at: saturncloud.ioStarting Price: $0.005 per GB per hour -
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Composable DataOps Platform
Composable Analytics
Composable is an enterprise-grade DataOps platform built for business users that want to architect data intelligence solutions and deliver operational data-driven products leveraging disparate data sources, live feeds, and event data regardless of the format or structure of the data. With a modern, intuitive dataflow visual designer, built-in services to facilitate data engineering, and a composable architecture that enables abstraction and integration of any software or analytical approach, Composable is the leading integrated development environment to discover, manage, transform and analyze enterprise data.Starting Price: $8/hr - pay-as-you-go -
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Domo
Domo
Domo puts data to work for everyone so they can multiply their impact on the business. Our cloud-native data experience platform goes beyond traditional business intelligence and analytics, making data visible and actionable with user-friendly dashboards and apps. Underpinned by a secure data foundation that connects with existing cloud and legacy systems, Domo helps companies optimize critical business processes at scale and in record time to spark the bold curiosity that powers exponential business results. -
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Snowflake
Snowflake
Snowflake is a comprehensive AI Data Cloud platform designed to eliminate data silos and simplify data architectures, enabling organizations to get more value from their data. The platform offers interoperable storage that provides near-infinite scale and access to diverse data sources, both inside and outside Snowflake. Its elastic compute engine delivers high performance for any number of users, workloads, and data volumes with seamless scalability. Snowflake’s Cortex AI accelerates enterprise AI by providing secure access to leading large language models (LLMs) and data chat services. The platform’s cloud services automate complex resource management, ensuring reliability and cost efficiency. Trusted by over 11,000 global customers across industries, Snowflake helps businesses collaborate on data, build data applications, and maintain a competitive edge.Starting Price: $2 compute/month -
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Dataiku
Dataiku
Dataiku is an advanced data science and machine learning platform designed to enable teams to build, deploy, and manage AI and analytics projects at scale. It empowers users, from data scientists to business analysts, to collaboratively create data pipelines, develop machine learning models, and prepare data using both visual and coding interfaces. Dataiku supports the entire AI lifecycle, offering tools for data preparation, model training, deployment, and monitoring. The platform also includes integrations for advanced capabilities like generative AI, helping organizations innovate and deploy AI solutions across industries. -
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Coder
Coder
Coder delivers self-hosted cloud development environments consistently provisioned as code and pre-deployed for developer activity on day one. Preferred by enterprises, Coder is open source and runs air-gapped on-premise or in your cloud, giving developers access to powerful infrastructure without compromising governance. Coder moves local development and source code to your centralized infrastructure where developers can access their remote environments via their favorite desktop or web-based IDE. This is the optimal intersection of improved developer experience, productivity, and security. Coder’s ephemeral development environments are provisioned as code from pre-defined templates, which means developers can create a new workspace with a click. Now, they can avoid days or weeks struggling with local dependency versioning conflicts or security approvals. With Coder, developers can onboard or shift between projects in minutes. -
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Comet
Comet
Manage and optimize models across the entire ML lifecycle, from experiment tracking to monitoring models in production. Achieve your goals faster with the platform built to meet the intense demands of enterprise teams deploying ML at scale. Supports your deployment strategy whether it’s private cloud, on-premise servers, or hybrid. Add two lines of code to your notebook or script and start tracking your experiments. Works wherever you run your code, with any machine learning library, and for any machine learning task. Easily compare experiments—code, hyperparameters, metrics, predictions, dependencies, system metrics, and more—to understand differences in model performance. Monitor your models during every step from training to production. Get alerts when something is amiss, and debug your models to address the issue. Increase productivity, collaboration, and visibility across all teams and stakeholders.Starting Price: $179 per user per month -
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Intel Tiber AI Studio
Intel
Intel® Tiber™ AI Studio is a comprehensive machine learning operating system that unifies and simplifies the AI development process. The platform supports a wide range of AI workloads, providing a hybrid and multi-cloud infrastructure that accelerates ML pipeline development, model training, and deployment. With its native Kubernetes orchestration and meta-scheduler, Tiber™ AI Studio offers complete flexibility in managing on-prem and cloud resources. Its scalable MLOps solution enables data scientists to easily experiment, collaborate, and automate their ML workflows while ensuring efficient and cost-effective utilization of resources. -
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With SAS Visual Statistics, multiple users can explore data, then interactively create and refine predictive models. Your data scientists and statisticians can act on observations at a granular level using the most appropriate analytical modeling techniques. The result? You'll unearth insights at unprecedented speeds, and find new ways to grow revenue. Easily build and refine models to target specific groups or segments, and run numerous scenarios simultaneously. You can ask more what-if questions to get better results. And put results into action with an automatically generated score code. Empower multiple users to interact with data visually – to add or change variables, remove outliers, etc. Instantly see how changes affect your model's predictive power, and make refinements quickly. Data science teams have the ultimate flexibility of working in their language of choice, so they can use their skills to the fullest. SAS Visual Statistics unites all analytical assets.
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SAS Viya
SAS
SAS® Viya® data science offerings provide a comprehensive, scalable analytics environment that's quick and easy to deploy, enabling you to meet diverse business needs. Automatically generated insights enable you to identify the most common variables across all models, the most important variables selected across models and assessment results for all models. Natural language generation capabilities are used to create project summaries written in plain language, enabling you to easily interpret reports. Analytics team members can add project notes to the insights report to facilitate communication and collaboration among team members. SAS lets you embed open source code within an analysis and call open source algorithms seamlessly within its environment. This facilitates collaboration across your organization because users can program in their language of choice. You can also take advantage of SAS Deep Learning with Python (DLPy), our open-source package on GitHub. -
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Zerve AI
Zerve AI
Merging the best of a notebook and an IDE into one integrated coding environment, experts can explore their data and write stable code at the same time with fully automated cloud infrastructure. Zerve’s data science development environment gives data science and ML teams a unified space to explore, collaborate, build, and deploy data science & AI projects like never before. Zerve offers true language interoperability, meaning that as well as being able to use Python, R, SQL, or Markdown all in the same canvas, users can connect these code blocks to each other. No more long-running code blocks or containers, with Zerve enjoying unlimited parallelization at any stage of the development journey. Analysis artifacts are automatically serialized, versioned, stored, and preserved for later use, meaning easily changing a step in the data flow without needing to rerun any preceding steps. Fine-grained selection of compute resources and extra memory for complex data transformation. -
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FeatureByte
FeatureByte
FeatureByte is your AI data scientist streamlining the entire lifecycle so that what once took months now happens in hours. Deployed natively on Databricks, Snowflake, BigQuery, or Spark, it automates feature engineering, ideation, cataloging, custom UDFs (including transformer support), evaluation, selection, historical backfill, deployment, and serving (online or batch), all within a unified platform. FeatureByte’s GenAI‑inspired agents, data, domain, MLOps, and data science agents interactively guide teams through data acquisition, quality, feature generation, model creation, deployment orchestration, and continued monitoring. FeatureByte’s SDK and intuitive UI enable automated and semi‑automated feature ideation, customizable pipelines, cataloging, lineage tracking, approval flows, RBAC, alerts, and version control, empowering teams to build, refine, document, and serve features rapidly and reliably. -
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Databricks Data Intelligence Platform
Databricks
The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker. -
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BDB Platform
Big Data BizViz
BDB is a modern data analytics and BI platform which can skillfully dive deep into your data to provide actionable insights. It is deployable on the cloud as well as on-premise. Our exclusive microservices based architecture has the elements of Data Preparation, Predictive, Pipeline and Dashboard designer to provide customized solutions and scalable analytics to different industries. BDB’s strong NLP based search enables the user to unleash the power of data on desktop, tablets and mobile as well. BDB has various ingrained data connectors, and it can connect to multiple commonly used data sources, applications, third party API’s, IoT, social media, etc. in real-time. It lets you connect to RDBMS, Big data, FTP/ SFTP Server, flat files, web services, etc. and manage structured, semi-structured as well as unstructured data. Start your journey to advanced analytics today. -
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Peak
Peak
A new decision intelligence system, putting AI in the hands of commercial leaders to drive great decision making. CODI, our Connected Decision Intelligence system, has been engineered by Peak to become a layer of intelligence that sits between your other systems, unleashing the power of your data for the first time. CODI enables you to quickly deploy AI solutions, harnessing the true potential of your data thanks to its unique full-stack features. It allows data science and data engineering teams to take full control of every aspect of building and deploying AI solutions, at speed and at scale. With CODI, AI projects move beyond being just experiments and become fully-deployed solutions that deliver real world value and results. Built on enterprise-grade infrastructure, CODI is capable of handling data at scale, and seamlessly integrates into existing tech stacks. Surface more insight and combine data from across your organization. -
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Amadea
ISoft
Amadea technology relies on the fastest real-time calculation and modeling engine on the market. Speed up the creation, deployment and automation of your analytics projects within the same integrated environment. Data quality is the key to analytical projects. Thanks to the ISoft real-time calculation engine, the fastest on the market, Amadea allows companies to prepare and use massive and/or complex data in real-time, regardless of the volume. ISoft started from a simple observation, successful analytical projects must involve the business users at every stage. Founded on a no-code interface, accessible to all types of users, Amadea allows everyone involved in analytical projects to take part. As Amadea has the fastest real-time calculation engine on the market, it lets you specify, prototype and build your data applications simultaneously. Amadea incorporates the fastest real-time data analysis engine on the market, 10 million lines per second & per core for standard calculations. -
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StreamFlux
Fractal
Data is crucial when it comes to building, streamlining and growing your business. However, getting the full value out of data can be a challenge, many organizations are faced with poor access to data, incompatible tools, spiraling costs and slow results. Simply put, leaders who can turn raw data into real results will thrive in today’s landscape. The key to this is empowering everyone across your business to be able to analyze, build and collaborate on end-to-end AI and machine learning solutions in one place, fast. Streamflux is a one-stop shop to meet your data analytics and AI challenges. Our self-serve platform allows you the freedom to build end-to-end data solutions, uses models to answer complex questions and assesses user behaviors. Whether you’re predicting customer churn and future revenue, or generating recommendations, you can go from raw data to genuine business impact in days, not months. -
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PurpleCube
PurpleCube
Enterprise-grade architecture and cloud data platform powered by Snowflake® to securely store and leverage your data in the cloud. Built-in ETL and drag-and-drop visual workflow designer to connect, clean & transform your data from 250+ data sources. Use the latest in Search and AI-driven technology to generate insights and actionable analytics from your data in seconds. Leverage our AI/ML environments to build, tune and deploy your models for predictive analytics and forecasting. Leverage our built-in AI/ML environments to take your data to the next level. Create, train, tune and deploy your AI models for predictive analysis and forecasting, using the PurpleCube Data Science module. Build BI visualizations with PurpleCube Analytics, search through your data using natural language, and leverage AI-driven insights and smart suggestions that deliver answers to questions you didn’t think to ask. -
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UBIX
UBIX
Ubiquitous real-time business decisions without the need for specialized tools and resources. UBIX is a pioneer at the intersection of generative AI and reinforcement learning driving business-led actionable insights and automation. Our patented no-code SaaS platform contextualizes and presents data from inside and outside the enterprise in minutes, not days, ensuring AI and ML innovation transformation. Improve daily decisions that impact productivity, waste, compliance, growth, and profitability. Get the right data to the right business leader at the right time in the right format. In just 5 steps and a couple of days, you can AI-enable your enterprise. Enhance business intelligence initiatives and free data scientists to innovate rather than serve reports. Artificial intelligence is no longer reserved for large organizations and technical teams, it’s for everyone at organizations of all sizes. UBIX makes artificial intelligence and advanced analytics available to everyone. -
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Amazon SageMaker Unified Studio is a comprehensive, AI and data development environment designed to streamline workflows and simplify the process of building and deploying machine learning models. Built on Amazon DataZone, it integrates various AWS analytics and AI/ML services, such as Amazon EMR, AWS Glue, and Amazon Bedrock, into a single platform. Users can discover, access, and process data from various sources like Amazon S3 and Redshift, and develop generative AI applications. With tools for model development, governance, MLOps, and AI customization, SageMaker Unified Studio provides an efficient, secure, and collaborative environment for data teams.
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Daft
Daft
Daft is a framework for ETL, analytics and ML/AI at scale. Its familiar Python dataframe API is built to outperform Spark in performance and ease of use. Daft plugs directly into your ML/AI stack through efficient zero-copy integrations with essential Python libraries such as Pytorch and Ray. It also allows requesting GPUs as a resource for running models. Daft runs locally with a lightweight multithreaded backend. When your local machine is no longer sufficient, it scales seamlessly to run out-of-core on a distributed cluster. Daft can handle User-Defined Functions (UDFs) in columns, allowing you to apply complex expressions and operations to Python objects with the full flexibility required for ML/AI. Daft runs locally with a lightweight multithreaded backend. When your local machine is no longer sufficient, it scales seamlessly to run out-of-core on a distributed cluster. -
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ZinkML
ZinkML Technologies
ZinkML is a zero-code data science platform designed to address the challenges faced by organizations in leveraging data effectively. By providing a visual and intuitive interface, it eliminates the need for extensive coding expertise, making data science accessible to a broader range of users. ZinkML streamlines the entire data science lifecycle, from data ingestion and preparation to model building, deployment, and monitoring. Users can drag-and-drop components to create complex data pipelines, explore data visually, and build predictive models without writing a single line of code. The platform also offers automated feature engineering, model selection, and hyperparameter tuning, accelerating the model development process. Moreover, ZinkML provides robust collaboration features, enabling teams to work together seamlessly on data science projects. By democratizing data science, we empower companies to extract maximum value from their data and drive better decision-making.
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