List of the Top 21 Data Science Software for Amazon Web Services (AWS) in 2026

Saturn Cloud is a versatile AI and machine learning platform that operates seamlessly across various cloud environments. It empowers data teams and engineers to create, scale, and launch their AI and ML applications using any technology stack they prefer. This flexibility allows users to tailor their solutions to meet specific needs and optimally leverage their existing resources.

Composable serves as a robust DataOps platform tailored for enterprises, empowering business users to develop data-centric products and formulate data intelligence solutions. This platform enables the creation of data-driven offerings that utilize a variety of data sources, including live streams and event data, irrespective of their format or structure. With its intuitive and user-friendly visual editor for dataflows, Composable also features built-in services to streamline data engineering tasks, in addition to a composable architecture that promotes both abstraction and integration of diverse analytical or software methodologies. As a result, it stands out as the premier integrated development environment for the exploration, management, transformation, and analysis of enterprise-level data. Moreover, its versatility ensures that teams can adapt quickly to changing data needs and leverage insights effectively.

Domo empowers all users to leverage data effectively, enhancing their contributions to the organization. Built on a robust and secure data infrastructure, our cloud-based platform transforms data into visible and actionable insights through intuitive dashboards and applications. By facilitating the optimization of essential business processes swiftly and efficiently, Domo inspires innovative thinking that drives remarkable business outcomes. With the ability to harness data across various departments, organizations can foster a culture of data-driven decision-making that leads to sustained growth and success.

Snowflake is a leading AI Data Cloud platform designed to help organizations harness the full potential of their data by breaking down silos and streamlining data management with unmatched scale and simplicity. The platform’s interoperable storage capability offers near-infinite access to data across multiple clouds and regions, enabling seamless collaboration and analytics. Snowflake’s elastic compute engine ensures top-tier performance for diverse workloads, automatically scaling to meet demand and optimize costs. Cortex AI, Snowflake’s integrated AI service, provides enterprises secure access to industry-leading large language models and conversational AI capabilities to accelerate data-driven decision making. Snowflake’s comprehensive cloud services automate infrastructure management, helping businesses reduce operational complexity and improve reliability. Snowgrid extends data and app connectivity globally across regions and clouds with consistent security and governance. The Horizon Catalog is a powerful governance tool that ensures compliance, privacy, and controlled access to data assets. Snowflake Marketplace facilitates easy discovery and collaboration by connecting customers to vital data and applications within the AI Data Cloud ecosystem. Trusted by more than 11,000 customers globally, including leading brands across healthcare, finance, retail, and media, Snowflake drives innovation and competitive advantage. Their extensive developer resources, training, and community support empower organizations to build, deploy, and scale AI and data applications securely and efficiently.

Dataiku is an advanced enterprise AI platform that enables organizations to transition from disconnected AI initiatives to a unified, scalable, and governed AI ecosystem. It integrates people, data, and technology into a single collaborative environment where both business users and data experts can contribute to AI development. The platform supports the full lifecycle of AI projects, including data preparation, model building, deployment, and ongoing monitoring. Through powerful orchestration, Dataiku connects data pipelines, applications, and machine learning models to create seamless, automated workflows. Its governance framework ensures that all AI activities are transparent, compliant, and aligned with organizational standards, while also managing cost and risk effectively. Users can build and deploy AI agents grounded in real business data, enabling more accurate and impactful outcomes. The platform helps organizations replace manual processes and spreadsheets with intelligent, AI-driven analytics systems. It also facilitates the reuse and scaling of machine learning models across teams, breaking down silos and improving collaboration. Dataiku supports analytics modernization without disrupting existing systems, allowing companies to evolve at their own pace. With adoption across industries like healthcare, finance, and manufacturing, it has demonstrated measurable benefits such as time savings and revenue generation. Its flexible architecture allows enterprises to adapt quickly to changing business needs and emerging AI trends. Ultimately, Dataiku empowers organizations to operationalize AI at scale and drive sustained business value through intelligent decision-making.

Zerve is the agentic data workspace designed for anyone who works with data, from solo analysts, data scientists and business users alike. Zerve brings together exploration, advanced analysis, collaboration, and production deployment into a single AI-native environment, so that important data work doesn’t stall, break, or disappear. Zerve is used by data professionals in companies such as BBC, QVC, Dun & Bradstreet, Airbus, and many others. Zerve makes advanced data work accessible, durable, and deployable from day one, starting with the messy, real-world data most projects begin with. At the heart of Zerve is a new way for humans and AI agents to work together. Zerve’s AI agents understand the full context of a project and actively help plan, build, debug, and iterate across multi-step analyses. Agents can assist with tasks like cleaning and transforming data, identifying issues, and testing approaches, reducing the manual effort that slows teams down. This means working at a higher level of abstraction without being slowed by setup or syntax. With Zerve, you always have an expert data scientist at your side, guiding decisions, suggesting next steps, and taking action. Unlike traditional data notebooks, workflows in Zerve are reproducible and stable. Users can work across Python, SQL, and R in a single workspace, connect directly to databases, data lakes, and warehouses, and integrate with Git for version control. The built-in distributed computing engine powers massively parallel execution for large-scale analysis, simulations, and AI workloads, with multi-agent orchestration coordinating complex pipelines behind the scenes. Zerve can be used as SaaS, self-hosted, or even on-premise for regulated environments.

Coder provides self-hosted cloud development environments that are ready for immediate use by developers and provisioned as code. This solution is especially popular among enterprises, as it is open source and can be deployed either on-premise or in the cloud, maintaining robust infrastructure access while ensuring compliance with governance requirements. By centralizing development and source code management, Coder allows developers to connect to their remote environments using their favorite desktop or web-based integrated development environments (IDEs). This method significantly improves the overall developer experience, boosts productivity, and enhances security measures. Additionally, Coder features ephemeral development environments created from pre-defined templates, enabling developers to set up new workspaces in an instant. This efficiency minimizes the challenges associated with local dependency versioning and lengthy security approval processes, allowing developers to switch projects or onboard new ones within minutes. Furthermore, organizations can benefit from reduced setup times and increased flexibility in managing their development workflows.

Oversee and enhance models throughout the comprehensive machine learning lifecycle. This process encompasses tracking experiments, overseeing models in production, and additional functionalities. Tailored for the needs of large enterprise teams deploying machine learning at scale, the platform accommodates various deployment strategies, including private cloud, hybrid, or on-premise configurations. By simply inserting two lines of code into your notebook or script, you can initiate the tracking of your experiments seamlessly. Compatible with any machine learning library and for a variety of tasks, it allows you to assess differences in model performance through easy comparisons of code, hyperparameters, and metrics. From training to deployment, you can keep a close watch on your models, receiving alerts when issues arise so you can troubleshoot effectively. This solution fosters increased productivity, enhanced collaboration, and greater transparency among data scientists, their teams, and even business stakeholders, ultimately driving better decision-making across the organization. Additionally, the ability to visualize model performance trends can greatly aid in understanding long-term project impacts.

SAS Visual Statistics fosters collaborative data exploration, allowing multiple users to interactively create and refine predictive models. Data scientists and statisticians can apply the most appropriate analytical techniques to derive insights at an intricate level. As a result, insights can be discovered at impressive speeds, leading to new revenue growth opportunities. This platform permits the construction and optimization of models targeted at specific demographics or segments, while simultaneously exploring various scenarios. Such capabilities motivate users to raise numerous what-if questions to improve outcomes. Moreover, results can be operationalized through automatically generated score code, streamlining application processes. Users can visually manipulate the data by adding or modifying variables, removing outliers, and more, which enables them to instantly evaluate how changes affect the model's predictive accuracy, facilitating rapid adjustments. Data science teams benefit from the flexibility of working in their preferred programming languages, thereby maximizing their skill set. Ultimately, SAS Visual Statistics unifies all analytical resources into a holistic solution for data-driven decision-making. This integration creates an environment that nurtures innovation and expands the horizons of data analysis, enabling teams to push the limits of their analytical capabilities. Furthermore, the collaborative features of the platform enhance teamwork and knowledge sharing among users, driving better results through collective expertise.

SAS Viya is a comprehensive cloud-native data and AI platform that helps organizations unify analytics, artificial intelligence, data management, and governance within a single connected environment. The platform is built to support the complete data-to-decision lifecycle, allowing businesses to access, manage, analyze, deploy, and govern data-driven insights at enterprise scale. SAS Viya enables organizations to connect to data from multiple sources while maintaining transparency, auditability, lineage tracking, and compliance throughout AI and analytics workflows. Businesses can build, validate, and operationalize machine learning and AI models faster while ensuring fairness, explainability, and responsible governance practices. The platform also includes the SAS Viya MCP Server, which allows AI agents and copilots to securely leverage SAS capabilities for automated and intelligent decision-making. SAS Viya supports flexible deployment options across cloud, hybrid, and on-premises environments, giving organizations greater control over infrastructure and security requirements. The platform is designed to simplify complex workflows and improve collaboration between data scientists, analysts, developers, and business teams. SAS Viya accelerates productivity by streamlining model training, analytics deployment, and operational decision processes within one scalable ecosystem. Organizations across banking, healthcare, life sciences, government, and manufacturing use SAS Viya for applications such as fraud detection, forecasting, customer intelligence, inventory optimization, and clinical trial analytics. The platform also delivers advanced governance capabilities that help businesses maintain policy enforcement, legal defensibility, and regulatory compliance across the AI lifecycle. With built-in automation, extensive analytics functionality, and enterprise-grade governance, SAS Viya helps organizations turn data into trusted and actionable business outcomes.

FeatureByte serves as your AI-driven data scientist, transforming the entire data lifecycle so that tasks that once took months can now be completed in just a few hours. It integrates effortlessly with platforms such as Databricks, Snowflake, BigQuery, and Spark, while automating a multitude of tasks like feature engineering, ideation, cataloging, and the creation of custom UDFs, including support for transformers. Additionally, it facilitates evaluation, selection, historical backfill, deployment, and serving—whether online or in batch—all through a unified platform. The GenAI-inspired agents at FeatureByte work collaboratively with experts in data, domain, MLOps, and data science, providing guidance through critical processes such as data acquisition, quality assurance, feature generation, model creation, orchestration of deployments, and continuous monitoring. Furthermore, FeatureByte comes equipped with an SDK and a user-friendly interface that support both automated and semi-automated ideation of features, customizable pipelines, cataloging, lineage tracking, approval workflows, role-based access control, alerts, and version management. These features empower teams to quickly and effectively build, refine, document, and serve their features. In addition to enhancing operational efficiency, this all-encompassing solution ensures that teams remain agile in response to evolving data demands and uphold rigorous standards in their data practices. Ultimately, FeatureByte positions organizations to harness the full potential of their data assets while streamlining their workflows.

The Databricks Data Intelligence Platform empowers every individual within your organization to effectively utilize data and artificial intelligence. Built on a lakehouse architecture, it creates a unified and transparent foundation for comprehensive data management and governance, further enhanced by a Data Intelligence Engine that identifies the unique attributes of your data. Organizations that thrive across various industries will be those that effectively harness the potential of data and AI. Spanning a wide range of functions from ETL processes to data warehousing and generative AI, Databricks simplifies and accelerates the achievement of your data and AI aspirations. By integrating generative AI with the synergistic benefits of a lakehouse, Databricks energizes a Data Intelligence Engine that understands the specific semantics of your data. This capability allows the platform to automatically optimize performance and manage infrastructure in a way that is customized to the requirements of your organization. Moreover, the Data Intelligence Engine is designed to recognize the unique terminology of your business, making the search and exploration of new data as easy as asking a question to a peer, thereby enhancing collaboration and efficiency. This progressive approach not only reshapes how organizations engage with their data but also cultivates a culture of informed decision-making and deeper insights, ultimately leading to sustained competitive advantages.

BDB serves as a cutting-edge business intelligence and analytics platform that provides comprehensive data analysis and actionable insights. It is versatile enough to be implemented in both cloud environments and on-premise servers. Featuring a distinctive microservices architecture, BDB includes vital components like Data Preparation, Predictive Analytics, a Pipeline, and a customizable Dashboard designer, which allows for bespoke solutions and scalable analytical capabilities across diverse industries. The platform is enhanced by powerful NLP-driven search functionalities that enable users to effectively access and utilize data on desktops, tablets, and mobile devices alike. Furthermore, BDB comes with a plethora of built-in data connectors, ensuring seamless real-time access to a variety of commonly utilized data sources, applications, third-party APIs, IoT devices, and social media networks. It is designed to connect with RDBMS, Big Data infrastructures, FTP/SFTP servers, flat files, and web services, thereby adeptly managing structured, semi-structured, and unstructured data types. Start your exploration into advanced analytics today and discover how to maximize the potential of your data. By adopting BDB, you are stepping into the realm of future-oriented data-driven decision-making. This platform not only enhances efficiency but also empowers organizations to stay competitive in an increasingly data-centric world.

Introducing an innovative decision intelligence platform that enables business leaders to significantly improve their decision-making strategies. Our Connected Decision Intelligence system, referred to as CODI, has been carefully crafted by Peak to serve as an intelligence layer that connects diverse systems while unlocking unprecedented potential from your data. CODI facilitates the rapid deployment of AI solutions, allowing organizations to fully harness their data through its unique full-stack capabilities. It empowers both data scientists and engineers to oversee every aspect of the development and execution of AI applications in an efficient and scalable manner. With the adoption of CODI, AI projects transition from initial tests to fully functional solutions that deliver real-world results and benefits. Built on a solid enterprise-grade foundation, CODI is capable of handling large data sets and integrates seamlessly with existing technological frameworks. Moreover, it fosters deeper insights and incorporates data from various segments of your organization, ultimately enhancing strategies and overall performance. This cutting-edge methodology guarantees that organizations can make well-informed decisions based on thorough data analysis, driving significant improvements in operational effectiveness. As a result, businesses are better equipped to navigate complex challenges and seize new opportunities in a rapidly changing market.

Amadea technology leverages the fastest real-time calculation and modeling engine currently available, allowing for the swift creation, deployment, and automation of analytics projects on a cohesive platform. Ensuring high data quality is crucial for the success of any analytical initiative, and with the leading ISoft real-time calculation engine, Amadea empowers organizations to manage and utilize extensive and complex datasets instantly, regardless of their size. Acknowledging that successful analytical projects necessitate the active engagement of business users at every stage, ISoft was developed with this understanding at the forefront. Amadea features a user-friendly no-code interface that encourages involvement from all project stakeholders. The unmatched speed of Amadea's real-time calculation engine allows for the concurrent specification, prototyping, and development of data applications, optimizing overall efficiency. With the impressive ability to process up to 10 million lines per second per core for standard calculations, Amadea emerges as a formidable solution for data-driven organizations, ensuring that valuable insights can be accessed quickly and effectively. As a result, this cutting-edge technology not only enhances decision-making capabilities but also positions businesses to excel in a world increasingly dominated by data.

Data is crucial for the processes of establishing, optimizing, and growing a business. However, many organizations struggle to fully utilize their data due to challenges such as restricted access, incompatible tools, rising costs, and slow results. In essence, those who successfully turn raw data into actionable insights will thrive in today’s competitive market. A key factor in this transformation is allowing all team members to efficiently analyze, develop, and collaborate on comprehensive AI and machine learning initiatives within a cohesive platform. Streamflux provides an all-in-one solution for your data analytics and AI requirements. Our intuitive platform allows you to develop complete data solutions, apply models to complex questions, and assess user interactions effectively. Whether your goal is to predict customer churn, forecast future revenue, or create tailored recommendations, you can convert unprocessed data into significant business outcomes in just days rather than months. By utilizing our platform, companies can improve productivity and cultivate a culture centered around data-driven decision-making, ultimately leading to sustained growth and innovation. This commitment to leveraging data effectively can set your organization apart in a rapidly evolving landscape.

Discover a robust enterprise architecture and a cloud-based data platform powered by Snowflake® that facilitates secure data storage and management in the cloud. Featuring an integrated ETL process alongside an easy-to-use drag-and-drop visual workflow designer, you can seamlessly connect, cleanse, and transform data from more than 250 sources. Leverage state-of-the-art Search and AI technologies to swiftly produce insights and actionable analytics derived from your data in mere seconds. Take advantage of our sophisticated AI/ML environments to build, refine, and deploy predictive analytics and forecasting models with ease. Elevate your data capabilities even further with our all-encompassing AI/ML frameworks that empower you to design, train, and implement AI models via the PurpleCube Data Science module. Furthermore, create captivating BI visualizations using PurpleCube Analytics, delve into your data through natural language queries, and gain from AI-enhanced insights and intelligent recommendations that uncover answers to inquiries you may not have anticipated. This comprehensive strategy ensures that you are thoroughly prepared to make informed, data-driven decisions with both confidence and clarity, setting your organization on a path toward success. As you engage with this platform, you'll find that the possibilities for innovation and growth are virtually limitless.

Real-time business decision-making that is always within reach can be accomplished without the need for specialized tools or resources. UBIX emerges as a pioneer at the intersection of generative AI and reinforcement learning, enabling actionable insights and automation that align with business requirements. Our distinct no-code SaaS platform quickly contextualizes and visualizes data from various internal and external sources within minutes, transforming the landscape of AI and machine learning innovations. This strategy significantly enhances day-to-day decision-making, impacting productivity, waste management, compliance, growth, and overall profitability. We guarantee that the appropriate data is delivered to the relevant business leader at the perfect time and in the most suitable format. By adhering to just five straightforward steps over a few days, organizations can effortlessly incorporate AI capabilities into their workflows. This not only fortifies business intelligence initiatives but also allows data scientists to concentrate on innovative projects instead of mundane reporting duties. The capabilities of artificial intelligence are no longer limited to large corporations or specialized teams; they are now within reach for individuals in organizations of all sizes. As a result, with UBIX, advanced analytics and artificial intelligence transform into resources that everyone can leverage, democratizing access to cutting-edge technology across various sectors. This shift ultimately empowers organizations to make more informed decisions and drive greater success.

Amazon SageMaker Unified Studio is an all-in-one platform for AI and machine learning development, combining data discovery, processing, and model creation in one secure and collaborative environment. It integrates services like Amazon EMR, Amazon SageMaker, and Amazon Bedrock, allowing users to quickly access data, process it using SQL or ETL tools, and build machine learning models. SageMaker Unified Studio also simplifies the creation of generative AI applications, with customizable AI models and rapid deployment capabilities. Designed for both technical and business teams, it helps organizations streamline workflows, enhance collaboration, and speed up AI adoption.

Daft is a sophisticated framework tailored for ETL, analytics, and large-scale machine learning/artificial intelligence, featuring a user-friendly Python dataframe API that outperforms Spark in both speed and usability. It provides seamless integration with existing ML/AI systems through efficient zero-copy connections to critical Python libraries such as Pytorch and Ray, allowing for effective GPU allocation during model execution. Operating on a nimble multithreaded backend, Daft initially functions locally but can effortlessly shift to an out-of-core setup on a distributed cluster once the limitations of your local machine are reached. Furthermore, Daft enhances its functionality by supporting User-Defined Functions (UDFs) in columns, which facilitates the execution of complex expressions and operations on Python objects, offering the necessary flexibility for sophisticated ML/AI applications. Its robust scalability and adaptability solidify Daft as an indispensable tool for data processing and analytical tasks across diverse environments, making it a favorable choice for developers and data scientists alike.

ZinkML serves as an open-source platform for data science that eliminates the need for coding, enabling organizations to utilize their data more effectively. Its user-friendly and visual interface is tailored to ensure that individuals without extensive programming knowledge can engage with data science, thus broadening accessibility. The platform simplifies the entire data science workflow, covering everything from data ingestion to model building, deployment, and monitoring. Users can easily create intricate pipelines by dragging and dropping components, visualize their data, or develop predictive models—all without any coding skills. With features like automated model selection, feature engineering, and hyperparameter optimization, ZinkML significantly speeds up the model development process. Furthermore, ZinkML fosters collaborative efforts by providing tools that enable teams to work together seamlessly on their data science initiatives. By making data science more accessible, ZinkML empowers organizations to derive greater value from their data and enhance their decision-making capabilities, ultimately leading to improved business outcomes. This shift towards democratized data science is crucial in a world where data-driven decisions are becoming increasingly vital.