# Best Enterprise Low-Code Machine Learning Platforms Software *By [Adam Crivello](https://research.g2.com/insights/author/adam-crivello)* Products classified in the overall Low-Code Machine Learning Platforms category are similar in many regards and help companies of all sizes solve their business problems. However, enterprise business features, pricing, setup, and installation differ from businesses of other sizes, which is why we match buyers to the right Enterprise Business Low-Code Machine Learning Platforms to fit their needs. Compare product ratings based on reviews from enterprise users or connect with one of G2's buying advisors to find the right solutions within the Enterprise Business Low-Code Machine Learning Platforms category. In addition to qualifying for inclusion in the Low-Code Machine Learning Platforms Software category, to qualify for inclusion in the Enterprise Business Low-Code Machine Learning Platforms Software category, a product must have at least 10 reviews left by a reviewer from an enterprise business. ## G2 Grid® for Low-Code Machine Learning Platforms Software ![G2 Grid® for Low-Code Machine Learning Platforms Software plotting products by satisfaction and market presence](https://www.g2.com/categories/low-code-machine-learning-platforms/grids.png?focus%5B%5D=7150&focus%5B%5D=989&focus%5B%5D=1327283&focus%5B%5D=16291&focus%5B%5D=16295) Highlighted products: Dataiku, Alteryx, SAS Viya, KNIME, and Altair AI Studio. Underlying data: [Grid® JSON](https://www.g2.com/categories/low-code-machine-learning-platforms/grids.json?focus%5B%5D=dataiku&focus%5B%5D=alteryx&focus%5B%5D=sas-sas-viya&focus%5B%5D=knime-analytics-platform&focus%5B%5D=rapidminer-studio&segment=enterprise) ## How Many Low-Code Machine Learning Platforms Software Products Does G2 Track? **Total Products under this Category:** 21 ### Category Stats (Jul 2026) - **Average Rating**: 4.39/5 The average rating of products in this category, based on all submitted ratings - **Top Trending Product**: KNIME (+1.56%) - Among all products in this category, KNIME recorded the largest rating increase compared to last month *Last updated: July 16, 2026* ## How Does G2 Rank Low-Code Machine Learning Platforms Software Products? **Why You Can Trust G2's Software Rankings:** - 30 Analysts and Data Experts - 3,700+ Authentic Reviews - 21+ Products - Unbiased Rankings G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category. --- **Sponsored** ### Alteryx Alteryx, through it's Alteryx One platform, helps enterprises transform complex, disconnected data into a clean, AI-ready state. Whether you’re creating financial forecasts, analyzing supplier performance, segmenting customer data, analyzing employee retention, or building competitive AI applications from your proprietary data, Alteryx One makes it easy to cleanse, blend, and analyze data to unlock the unique insights that drive impactful decisions. AI-Guided Analytics Alteryx automates and simplifies every stage of data preparation and analysis, from validation and enrichment to predictive analytics and automated insights. Incorporate generative AI directly into your workflows to streamline complex data tasks and generate insights faster. Unmatched flexibility, whether you prefer code-free workflows, natural language commands, or low-code options, Alteryx adapts to your needs. Trusted. Secure. Enterprise-Ready. Alteryx is trusted by over half of the Global 2000 and 19 of the top 20 global banks. With built-in automation, governance, and security, your workflows can scale and maintain compliance while delivering consistent results. And it doesn’t matter if your systems are on-premises, hybrid, or in the cloud; Alteryx fits effortlessly into your infrastructure. Easy to Use. Deeply Connected. What truly sets Alteryx apart is our focus on efficiency and ease of use for analysts and our active community of 700,000 Alteryx users to support you at every step of your journey. With seamless integration to data everywhere including platforms like Databricks, Snowflake, AWS, Google, SAP, and Salesforce, our platform helps unify siloed data and accelerate getting to insights. Visit Alteryx.com for more information, and to start your free trial. [Visit website](https://www.g2.com/external_clickthroughs/record?secure%5Bad_program%5D=ppc&secure%5Bad_slot%5D=category_product_list&secure%5Bcategory_id%5D=1011941&secure%5Bchosen_at%5D=2026-07-17T05%3A30%3A18Z&secure%5Bdisplayable_resource_id%5D=1011941&secure%5Bdisplayable_resource_type%5D=Category&secure%5Bmedium%5D=sponsored&secure%5Bplacement_reason%5D=page_category&secure%5Bplacement_resource_ids%5D%5B%5D=1011941&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=989&secure%5Bresource_id%5D=1011941&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Flow-code-machine-learning-platforms%2Fenterprise%3Fopen_modal_url%3D%252Fproducts%252Fsas-sas-viya%252Fwishlists%253Fhost_path%253D%25252Fcategories%25252Flow-code-machine-learning-platforms%25252Fenterprise%2526source%253Dcategory&secure%5Btoken%5D=7aa8abd2e32b7cbb927ecef160b12b717a0ff403c1e4a141fe82fb495fde75e6&secure%5Burl%5D=https%3A%2F%2Fwww.alteryx.com%2Ftrial%3Futm_source%3Dg2%26utm_medium%3Dreviewsite%26utm_campaign%3DFY25_Global_AllRegions_AlwaysOn_AllPersonas_IndustryAgnostic%26utm_content%3Dg2_freetrial&secure%5Burl_type%5D=free_trial) --- ## What Are the Top-Rated Low-Code Machine Learning Platforms Software Products in 2026? ### 1. [Dataiku](https://www.g2.com/products/dataiku/reviews) Dataiku is the Platform for AI Success: the AI orchestration layer where enterprises build, deploy, and govern analytics, models, and agents at scale. It sits on top of the data platforms, clouds, and AI services you already use, working across all of them without locking you into any one. Dataiku expands who can build production AI, putting the right tools in the hands of data scientists and domain experts alike, from fraud analysts to demand planners. It orchestrates machine learning, rules, LLMs, and agents as one governed system, built on more than a decade of running production AI. Governance is part of the build rather than something bolted on afterward, so teams ship faster while keeping performance, cost, and risk under control. The result: AI that moves from experimentation to trusted, measurable execution now, not in 18 months. **Average Rating:** 4.4/5.0 **Total Reviews:** 210 **Who Is the Company Behind Dataiku?** - **Seller:** [Dataiku](https://www.g2.com/sellers/dataiku) - **Company Website:** https://Dataiku.com - **Year Founded:** 2013 - **HQ Location:** New York, NY - **Twitter:** @dataiku (22,917 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/dataiku/ (1,619 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Scientist, Data Analyst - **Top Industries:** Financial Services, Pharmaceuticals - **Company Size:** 60% Enterprise, 22% Mid-Market #### What Are Dataiku's Pros and Cons? **Pros:** - Features (80 reviews) - Ease of Use (79 reviews) - Usability (45 reviews) - Easy Integrations (43 reviews) - Productivity Improvement (41 reviews) **Cons:** - Learning Curve (43 reviews) - Steep Learning Curve (25 reviews) - Difficult Learning (23 reviews) - Slow Performance (23 reviews) - Expensive (22 reviews) ### What Do G2 Reviewers Say About Dataiku? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate how **Dataiku simplifies ML development** , enabling quick model training and evaluation while accepting various data formats. - Users find Dataiku's **ease of use** invaluable, simplifying data integration and making machine learning development straightforward. - Users appreciate the **ease of use** in Dataiku, enabling collaboration between technical and non-technical users seamlessly. - Users value the **easy integrations** of Dataiku, facilitating collaboration and streamlining the entire data pipeline process. - Users benefit from the **significant productivity improvement** provided by Dataiku's visual recipes and collaborative environment. **Cons:** - Users find the **steep learning curve** challenging for beginners, making initial experience difficult. - Users find the **steep learning curve** challenging, especially when mastering advanced features as beginners. - Users find the **difficult learning** curve challenging, especially for beginners trying to utilize advanced features effectively. - Users report **slow performance** with Dataiku, particularly when managing large datasets and experiencing UI lag in projects. - Users find Dataiku to be **expensive** , particularly challenging for small companies and beginners due to high costs. #### What Are Recent G2 Reviews of Dataiku? **"[Build Faster Workflows with Connected Data from many providers or distinct data sources](https://www.g2.com/survey_responses/dataiku-review-13120436)"** **Rating:** 4.5/5.0 stars *— Adalberto G.* [Read full review](https://www.g2.com/survey_responses/dataiku-review-13120436) --- **"[Intuitive and Powerful for Machine Learning Experiments](https://www.g2.com/survey_responses/dataiku-review-13117166)"** **Rating:** 4.5/5.0 stars *— jimena m.* [Read full review](https://www.g2.com/survey_responses/dataiku-review-13117166) --- #### What Are G2 Users Discussing About Dataiku? - [Is Dataiku an ETL tool?](https://www.g2.com/discussions/is-dataiku-an-etl-tool) - [Is Dataiku web based?](https://www.g2.com/discussions/is-dataiku-web-based) - [What is DSS Dataiku?](https://www.g2.com/discussions/what-is-dss-dataiku) - [What is Dataiku DSS used for?](https://www.g2.com/discussions/what-is-dataiku-dss-used-for) ### 2. [Alteryx](https://www.g2.com/products/alteryx/reviews) Alteryx, through it's Alteryx One platform, helps enterprises transform complex, disconnected data into a clean, AI-ready state. Whether you’re creating financial forecasts, analyzing supplier performance, segmenting customer data, analyzing employee retention, or building competitive AI applications from your proprietary data, Alteryx One makes it easy to cleanse, blend, and analyze data to unlock the unique insights that drive impactful decisions. AI-Guided Analytics Alteryx automates and simplifies every stage of data preparation and analysis, from validation and enrichment to predictive analytics and automated insights. Incorporate generative AI directly into your workflows to streamline complex data tasks and generate insights faster. Unmatched flexibility, whether you prefer code-free workflows, natural language commands, or low-code options, Alteryx adapts to your needs. Trusted. Secure. Enterprise-Ready. Alteryx is trusted by over half of the Global 2000 and 19 of the top 20 global banks. With built-in automation, governance, and security, your workflows can scale and maintain compliance while delivering consistent results. And it doesn’t matter if your systems are on-premises, hybrid, or in the cloud; Alteryx fits effortlessly into your infrastructure. Easy to Use. Deeply Connected. What truly sets Alteryx apart is our focus on efficiency and ease of use for analysts and our active community of 700,000 Alteryx users to support you at every step of your journey. With seamless integration to data everywhere including platforms like Databricks, Snowflake, AWS, Google, SAP, and Salesforce, our platform helps unify siloed data and accelerate getting to insights. Visit Alteryx.com for more information, and to start your free trial. **Average Rating:** 4.6/5.0 **Total Reviews:** 845 **Who Is the Company Behind Alteryx?** - **Seller:** [Alteryx](https://www.g2.com/sellers/alteryx) - **Company Website:** https://www.alteryx.com - **Year Founded:** 1997 - **HQ Location:** Irvine, CA - **Twitter:** @alteryx (26,149 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/903031/ (2,304 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Analyst, Analyst - **Top Industries:** Financial Services, Accounting - **Company Size:** 63% Enterprise, 21% Mid-Market #### What Are Alteryx's Pros and Cons? **Pros:** - Ease of Use (333 reviews) - Automation (148 reviews) - Intuitive (132 reviews) - Easy Learning (102 reviews) - Efficiency (102 reviews) **Cons:** - Expensive (88 reviews) - Learning Curve (80 reviews) - Missing Features (62 reviews) - Learning Difficulty (55 reviews) - Slow Performance (41 reviews) ### What Do G2 Reviewers Say About Alteryx? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **ease of use** of Alteryx, making data manipulation simple and accessible for everyone. - Users appreciate the **efficient automation** in Alteryx, significantly speeding up their data preparation and analysis tasks. - Users find Alteryx to be **very intuitive** , making technology accessible and easy to learn for everyone. - Users find Alteryx to be **easy to learn and use** , with intuitive tools that enhance workflow efficiency. - Users value the **efficiency** of Alteryx, effortlessly managing and processing data for streamlined analysis. **Cons:** - Users find Alteryx's licensing to be **expensive** , especially challenging for small teams and startups to justify costs. - Users note a **learning curve** for mastering advanced features, which can be challenging for beginners. - Users feel the **missing features** in Alteryx hinder performance, requiring additional tools like Tableau for effective reporting. - Users note a **steep learning curve** for Alteryx, particularly those accustomed to hardcore SQL practices. - Users report that **slow performance** with large workflows hampers analysis and complicates data wrangling tasks. #### What Are Recent G2 Reviews of Alteryx? **"[Alteryx Streamlines Data Prep with an Intuitive Drag-and-Drop Workflow Builder](https://www.g2.com/survey_responses/alteryx-review-13000974)"** **Rating:** 4.5/5.0 stars *— Ankit K.* [Read full review](https://www.g2.com/survey_responses/alteryx-review-13000974) --- **"[Intuitive Drag-and-Drop Analytics That Speeds Up Data Prep and Insights](https://www.g2.com/survey_responses/alteryx-review-12983224)"** **Rating:** 4.5/5.0 stars *— Akhil S.* [Read full review](https://www.g2.com/survey_responses/alteryx-review-12983224) --- ### 3. [SAS Viya](https://www.g2.com/products/sas-sas-viya/reviews) SAS Viya is a cloud-native data and AI platform that enables teams to build, deploy and scale explainable AI that drives trusted, confident decisions. It unites the entire data and AI life cycle and empowers teams to innovate quickly while balancing speed, automation and governance by design. Viya unifies data management, advanced analytics and decisioning in a single platform, so organizations can move from experimentation to production with confidence, delivering measurable business impact that is secure, explainable and scalable across any environment. Key capabilities required to deliver trusted decisions include: • End-to-end clarity across the data and AI life cycle, with built-in lineage, auditability and continuous monitoring to support defensible decisions. • Governance by design, enabling consistent oversight across data, models and decisions to reduce risk and accelerate adoption. • Explainable AI at scale, so insights and outcomes can be understood, validated and trusted by business and regulators alike. • Operationalized analytics, ensuring value continues beyond deployment through monitoring, retraining and life cycle management. • Flexible, cloud-native deployment, allowing organizations to start anywhere and scale everywhere while maintaining control. **Average Rating:** 4.3/5.0 **Total Reviews:** 769 **Who Is the Company Behind SAS Viya?** - **Seller:** [SAS Institute Inc.](https://www.g2.com/sellers/sas-institute-inc-df6dde22-a5e5-4913-8b21-4fa0c6c5c7c2) - **Company Website:** https://www.sas.com/ - **Year Founded:** 1976 - **HQ Location:** Cary, NC - **Twitter:** @SASsoftware (60,863 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1491/ (18,638 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Student, Biostatistician - **Top Industries:** Pharmaceuticals, Banking - **Company Size:** 33% Small-Business, 33% Enterprise #### What Are SAS Viya's Pros and Cons? **Pros:** - Ease of Use (234 reviews) - Features (218 reviews) - Analytics (196 reviews) - Data Analysis (166 reviews) - Intuitive (145 reviews) **Cons:** - Learning Difficulty (151 reviews) - Learning Curve (144 reviews) - Complexity (143 reviews) - Difficult Learning (117 reviews) - Expensive (108 reviews) ### What Do G2 Reviewers Say About SAS Viya? *AI-generated summary from verified user reviews* **Pros:** - Users value the **user-friendly interface** of SAS Viya, which simplifies data analysis for all proficiency levels. - Users praise SAS Viya for its **advanced analytical capabilities** , enabling real-time insights and decision-making across various industries. - Users value the **advanced analytical capabilities** of SAS Viya, enhancing decision-making and providing deep business insights. - Users value the **end-to-end data lifecycle tooling** of SAS Viya, enhancing insights and decision-making across our organization. - Users value the **high performance efficiency** of SAS Viya, noting its speed and effectiveness in handling large data sets. **Cons:** - Users find SAS Viya **difficult to use for non-technical users** , impacting their ability to access reports and dashboards. - Users find the **learning curve steep** , making it challenging for non-technical users to utilize SAS Viya effectively. - Users find the **visualization complexity** of SAS Viya challenging, especially for non-technical and new users. - Users find the **difficult learning curve** challenging, especially for non-technical users accessing reports and dashboards. - Users find the **pricing to be expensive** and often unclear, making it a significant concern during assessment. #### What Are Recent G2 Reviews of SAS Viya? **"[Powerful Integration, Effortless Customization](https://www.g2.com/survey_responses/sas-viya-review-13109700)"** **Rating:** 5.0/5.0 stars *— 🇮🇳 Jaimit N.* [Read full review](https://www.g2.com/survey_responses/sas-viya-review-13109700) --- **"[Effective Data Analysis with SAS Viya](https://www.g2.com/survey_responses/sas-viya-review-11872818)"** **Rating:** 4.5/5.0 stars *— Fungai J.* [Read full review](https://www.g2.com/survey_responses/sas-viya-review-11872818) --- #### What Are G2 Users Discussing About SAS Viya? - [What is SAS Visual Data Mining and Machine Learning used for?](https://www.g2.com/discussions/what-is-sas-visual-data-mining-and-machine-learning-used-for) - 2 comments ### 4. [KNIME](https://www.g2.com/products/knime-analytics-platform/reviews) KNIME helps everybody make sense of data. Its free and open source KNIME Analytics Platform enables anyone — whether they come from a business, technical or data background — to intuitively work with data, every day. KNIME Business Hub is the commercial complement to KNIME Analytics Platform and enables users to collaborate on data science and share insights across the organization. Together, the products support the complete data science lifecycle, allowing teams at all levels of analytics readiness to support the operationalization of data and to build a scalable data science practice. **Average Rating:** 4.5/5.0 **Total Reviews:** 100 **Who Is the Company Behind KNIME?** - **Seller:** [KNIME](https://www.g2.com/sellers/knime) - **Company Website:** https://knime.com - **Year Founded:** 2008 - **HQ Location:** Zurich, Switzerland - **Twitter:** @knime (7,998 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/692207?trk=tyah&trkInfo=clickedVertical%3Acompany%2CclickedEntityId%3A692207%2Cidx%3A2-1-4%2CtarId%3A1454002156993%2Ctas%3Aknime (244 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Information Technology and Services, Higher Education - **Company Size:** 42% Enterprise, 33% Mid-Market #### What Are KNIME's Pros and Cons? **Pros:** - Ease of Use (7 reviews) - Coding Ease (4 reviews) - Ease of Learning (4 reviews) - Learning (4 reviews) - Data Visualization (3 reviews) **Cons:** - Learning Difficulty (3 reviews) - Memory Usage (3 reviews) - Storage Limitations (3 reviews) - Data Management Issues (2 reviews) - Insufficient Learning Resources (2 reviews) ### What Do G2 Reviewers Say About KNIME? *AI-generated summary from verified user reviews* **Pros:** - Users find **KNIME's ease of use** remarkable, enabling effortless workflow creation without coding expertise. - Users value the **coding ease** of KNIME, making it accessible for beginners and non-technical users alike. - Users find KNIME to be an **easy-to-learn platform** that enables quick delivery of data solutions without coding expertise. - Users find KNIME to be **easy to learn** , enabling quick delivery of complex data analysis and AI solutions. - Users praise the **intuitive data visualization capabilities** of KNIME, making complex data insights easily accessible. **Cons:** - Users find the **learning difficulty** of KNIME challenging, particularly with unfamiliar data science concepts and visual programming. - Users often face **memory usage issues** with KNIME, leading to slow performance and difficulties handling large files. - Users face **storage limitations** with KNIME, leading to memory issues and slow performance with large files. - Users find **data management issues** with KNIME, particularly in improving file handling and accessing certain databases. - Users find the **lack of learning resources** for KNIME frustrating, hindering their ability to effectively utilize the software. #### What Are Recent G2 Reviews of KNIME? **"[KNIME’s Visual Workflows - One of the best tool for Auditing, Accounting & Finance Professionals](https://www.g2.com/survey_responses/knime-review-12976842)"** **Rating:** 5.0/5.0 stars *— Charm M.* [Read full review](https://www.g2.com/survey_responses/knime-review-12976842) --- **"[KNIME’s Free No-Code Drag-and-Drop Analytics, from Descriptive to Agentic AI](https://www.g2.com/survey_responses/knime-review-12992618)"** **Rating:** 5.0/5.0 stars *— Guylaine B.* [Read full review](https://www.g2.com/survey_responses/knime-review-12992618) --- #### What Are G2 Users Discussing About KNIME? - [What is KNIME Analytics Platform used for?](https://www.g2.com/discussions/what-is-knime-analytics-platform-used-for) - [Is Knime easy to use?](https://www.g2.com/discussions/is-knime-easy-to-use) - 1 comment - [How do I use Knime Analytics?](https://www.g2.com/discussions/how-do-i-use-knime-analytics) - [Is Knime any good?](https://www.g2.com/discussions/is-knime-any-good) - [What is Knime analytics platform?](https://www.g2.com/discussions/what-is-knime-analytics-platform) ### 5. [Altair AI Studio](https://www.g2.com/products/rapidminer-studio/reviews) Altair AI Studio (formerly RapidMiner Studio) is a data science tool that anyone can use to design and prototype highly explainable AI and machine learning models that help build trust throughout an organization. Altair AI Studio includes: - Full generative AI functionality with access to hundreds of large language models (LLMs). - Intuitive and powerful drag-and-drop canvases that give users code-like control without complexity. - Award-winning auto ML with automated clustering, predictive modeling, feature engineering, and time series forecasting. - Data connectivity, exploration, and preparation. - Deploy and manage AI projects and models at enterprise scale. - Collaborate with team members in the same environment without having to worry about overwriting each other's work. - Unify the entire data science lifecycle from data exploration and machine learning to model operations and visualization and deploy in the cloud. Altair AI Studio helps users make powerful insights accessible to the entire organization and can scale seamlessly for users and enterprises. Altair AI studio enables organizations to derive significant value from AI with minimal cost and operational impact. **Average Rating:** 4.6/5.0 **Total Reviews:** 494 **Who Is the Company Behind Altair AI Studio?** - **Seller:** [Altair](https://www.g2.com/sellers/altair-186799f5-3238-493f-b3ad-b8cac484afd7) - **Company Website:** https://www.altair.com/ - **Year Founded:** 1985 - **HQ Location:** Troy, MI - **LinkedIn® Page:** https://www.linkedin.com/company/8323/ (2,774 employees on LinkedIn®) - **Ownership:** NASDAQ:ALTR **Who Uses This Product?** - **Who Uses This:** Student, Data Scientist - **Top Industries:** Higher Education, Education Management - **Company Size:** 42% Small-Business, 30% Mid-Market #### What Are Altair AI Studio's Pros and Cons? **Pros:** - Ease of Use (9 reviews) - Machine Learning (8 reviews) - AI Integration (6 reviews) - AI Technology (5 reviews) - Automation (5 reviews) **Cons:** - Complexity (4 reviews) - Large Dataset Handling (3 reviews) - Slow Performance (3 reviews) - Complexity Issues (2 reviews) - Complex Usage (2 reviews) ### What Do G2 Reviewers Say About Altair AI Studio? *AI-generated summary from verified user reviews* **Pros:** - Users praise the **ease of use** of Altair AI Studio, highlighting its intuitive drag-and-drop interface for data tasks. - Users enjoy the **no-code machine learning** capabilities of Altair AI Studio, making model building accessible and efficient. - Users appreciate the **advanced AI integration** of Altair AI Studio, enhancing decision-making and streamlining data processes. - Users value the **advanced machine learning and data analytics** of Altair AI Studio, enhancing decision-making and efficiency. - Users benefit from **automation** in Altair AI Studio, streamlining data processes and enhancing decision-making efficiency. **Cons:** - Users find the **complexity** of Altair AI Studio challenging, especially with language barriers and slow performance on large datasets. - Users report **slower performance with large datasets** , experiencing slowdowns and occasional UI bugs during complex operations. - Users experience **slow performance** when handling large datasets, leading to occasional slowdowns and UI issues. - Users find Altair AI Studio to have **complexity issues** due to language barriers and complicated support access. - Users find the **complex usage** of Altair AI Studio challenging, especially due to inadequate documentation for beginners. #### What Are Recent G2 Reviews of Altair AI Studio? **"[Great tool for easy data analysis and testing of AI models](https://www.g2.com/survey_responses/altair-ai-studio-review-12942088)"** **Rating:** 4.5/5.0 stars *— Sanjeet S.* [Read full review](https://www.g2.com/survey_responses/altair-ai-studio-review-12942088) --- **"[Essential Tool for Streamlined Sensor Analysis](https://www.g2.com/survey_responses/altair-ai-studio-review-12568188)"** **Rating:** 5.0/5.0 stars *— Ayçe M.* [Read full review](https://www.g2.com/survey_responses/altair-ai-studio-review-12568188) --- #### What Are G2 Users Discussing About Altair AI Studio? - [What is RapidMiner used for?](https://www.g2.com/discussions/what-is-rapidminer-used-for) - 1 comment - [What are the data mining tools?](https://www.g2.com/discussions/what-are-the-data-mining-tools) - [Is RapidMiner open source?](https://www.g2.com/discussions/is-rapidminer-open-source) - [How do you use the Rapid Miner?](https://www.g2.com/discussions/how-do-you-use-the-rapid-miner) - [Is Rapid Miner legit?](https://www.g2.com/discussions/is-rapid-miner-legit) ## What Is Low-Code Machine Learning Platforms Software? [Artificial Intelligence Software](https://www.g2.com/categories/artificial-intelligence) ## What Software Categories Are Similar to Low-Code Machine Learning Platforms Software? - [Predictive Analytics Software](https://www.g2.com/categories/predictive-analytics) - [Analytics Platforms](https://www.g2.com/categories/analytics-platforms) - [Machine Learning Software](https://www.g2.com/categories/machine-learning) - [Data Science and Machine Learning Platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms) - [MLOps Platforms](https://www.g2.com/categories/mlops-platforms) - [Generative AI Infrastructure Software](https://www.g2.com/categories/generative-ai-infrastructure) - [Large Language Model Operationalization (LLMOps) Software](https://www.g2.com/categories/large-language-model-operationalization-llmops) --- ## What Are the Most Common Questions About Low-Code Machine Learning Platforms Software? *AI-generated · Last updated: June 3, 2026* ### Which low code ml platform gives the best balance of price and automation features Based on G2 reviews, these products are the most consistently mentioned for low-code automation and model-building workflows. - [Alteryx](https://www.g2.com/products/alteryx) — automated data prep and reporting. - [SAS Viya](https://www.g2.com/products/sas-sas-viya) — automated ML pipelines and dashboards. - [Dataiku](https://www.g2.com/products/dataiku) — visual workflows with coding flexibility. - [Altair AI Studio](https://www.g2.com/products/rapidminer-studio) — AutoML with visual workflow design. ### Low code machine learning platforms that integrate well with existing web apps and APIs According to verified users, integration strength shows up in a few recurring patterns: API access, compatibility with existing cloud or business systems, and the ability to move data between tools without heavy custom work. Recent reviewers highlight platforms that connect to multiple data sources, support open languages or APIs, and fit into broader enterprise workflows. They also note that integration quality can vary by connector and environment, especially when teams need external systems, custom pipelines, or cross-cloud support. Buyers evaluating this area should look closely at how easily a platform handles ingestion, deployment, and workflow handoffs using the systems their team already depends on. ### What���s the easiest low code ml platform for a non data scientist to build models According to verified users, ease for non-data scientists usually comes from drag-and-drop design, guided workflows, and the option to build models without writing code. Recent G2 reviews frequently mention beginner-friendly interfaces, visual pipelines, AutoML support, and smoother onboarding when platforms balance simplicity with room to grow. Reviewers also point out that many products are approachable at first but still have learning curves once projects become more complex or datasets get larger. For buyers, the most practical signal is whether non-technical users can prepare data, test models, and share outputs without relying on specialists for every step of the workflow. ### What are the best low code machine learning platforms Based on G2 reviews, these products appear most often in recent feedback for low-code machine learning use cases. - [Alteryx](https://www.g2.com/products/alteryx) — drag-and-drop data prep and automation. - [SAS Viya](https://www.g2.com/products/sas-sas-viya) — visual modeling and governed analytics. - [Dataiku](https://www.g2.com/products/dataiku) — collaborative end-to-end ML workflows. - [Altair AI Studio](https://www.g2.com/products/rapidminer-studio) — no-code modeling for engineering data. ### What features define modern low-code machine learning platforms According to verified users, modern low-code machine learning platforms are defined by visual workflow building, automated model selection, data preparation tools, and the flexibility to mix no-code steps with code when needed. Recent reviews also repeatedly mention dashboarding, reporting, deployment support, model monitoring, collaboration, and integration with common data sources or APIs. Buyers should also weigh practical usability signals that come up often in reviews, such as onboarding experience, interface clarity, workflow speed, and how well the platform supports both technical and non-technical contributors. The strongest products tend to reduce manual work while keeping model building, data movement, and operational handoffs in one environment.