--- title: DataCanvas Reviews meta_title: 'DataCanvas Reviews 2026: Details, Pricing, & Features | G2' meta_description: Filter 10 reviews by the users' company size, role or industry to find out how DataCanvas works for a business like yours. aggregate_rating: rating_value: 4.8 review_count: 10 scale: '5' date_modified: '2025-10-31' parent_category: name: Artificial Intelligence url: https://www.g2.com/categories/artificial-intelligence --- # DataCanvas Reviews **Vendor:** DataCanvas **Category:** [Data Science and Machine Learning Platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms) **Average Rating:** 4.8/5.0 **Total Reviews:** 10 ## About DataCanvas Beijing ZetYun Technology Co., Ltd. (DataCanvas) was founded in 2013, focusing on the continuous development and construction of automatic data science platform, focusing on providing a complete set of development platform for data scientists and AI practitioners, and providing comprehensive supporting services for intelligent upgrading and transformation of government and enterprises. DataCanvas is a Chinese company independently researched and developed. Relying on the domestic and overseas leading data science platform, DataCanvas has provided real-time and agile AI capability construction for customers in government, finance, aviation, manufacturing, transportation, education, real estate, Internet and other industries. Through the DataCanvas platform, it can provide automatic machine learning analysis and real-time computing capabilities and help business analysts and data scientists quickly cooperate in development, and realize automatic model creation, management and application support. To create greater value for customer business on cutting-edge technologies and solutions such as technological innovation and artificial intelligence. The company has outstanding data scientists and product R & D team and has front edge industry practice experience in automatic deep machine learning, data modeling, big data analysis and other fields. In 2020, with the original DeepTables open-source project, DataCanvas won the first place in the world in the Kaggle competition among more than 1100 teams including well-known e-commerce companies and search engine companies. Headquartered in Beijing and facing the whole country, it has branches in Shanghai, Shandong and Shenzhen. ## DataCanvas Reviews ### 1. Efficient tool to process data in Real-Time **Rating:** 4.0/5.0 stars **Reviewed by:** sanfiya p. | Research Executive II, Mid-Market (51-1000 emp.) **Reviewed Date:** January 27, 2023 **What do you like best about DataCanvas?** DataCanvas is helpful in Real-time and offline business analytics. The main advantage of using DataCanvas is the User Interface is very smooth and friendly. The Data Scientist with Python knowledge can draw valuable and informative insights from DataCanvas. The modification can be made to the million of rows of data with ease using this tool. **What do you dislike about DataCanvas?** Nothing to dislike so far - DataCanvas can be further improved to provide weekly, monthly and yearly basis analytics to any specific projects that runs for lifetime. **What problems is DataCanvas solving and how is that benefiting you?** We do analytics on daily basis. DataCanvas play a critical role on it. The research project we conducted to analyse the recent trends in the talent market across various locations helped us to figure out most beneficial insights using DataCanvas. We gathered data from various sources. For instance, the population of specific location from various government portals, graduate data from various university websites, and the current location and designation of the talent from their public professional platforms. So, that the data are uneven and of different formats. The data analytics features in this tool helped us to process these data and gain evident insights. We can aslo be able to visualise this data and process these data in Real-time. The insights helps us to get the clear view of talent market and the possible growth of domains across various locations. ### 2. The ceiling of a one-stop data science platform integrating multiple functions **Rating:** 5.0/5.0 stars **Reviewed by:** 佳豪 . | researcher, Mid-Market (51-1000 emp.) **Reviewed Date:** June 07, 2022 **What do you like best about DataCanvas?** DataCanvas is a versatile, end-to-end machine learning platform for data science teams. As an end-to-end automated modeling platform, DataCanvas APS uses AI technology to deliver efficient, agile responses to business needs, enabling model development and application to align with industry scenarios, and addressing the challenges of generating, managing, and operating multiple business models on a large scale. Provide unified standard automation modeling capabilities and model lifecycle management functions, realize the operator open source to users, enabling enterprise customers to build independent AI capabilities. **What do you dislike about DataCanvas?** DataCanvas is well designed with no obvious flaws. **Recommendations to others considering DataCanvas:** Whether you are an engineer from an enterprise or a developer/student from a research institution, you can consult DataCanvas for data science and ML development.  Assess your own situation, including the requirements for the data science platform for each business scenario, the hardware and technical architecture, and the skill level acquired by employees.  If you're going to build a data science platform, you should look to DataCanvas for advice.  They have a lot of experience in this area, and they can offer the help of experienced data scientists.  It offers a full range of autonomous AI capabilities, independent of specific hardware or algorithm providers.  We hope that this product can continue to be optimized and upgraded, and keep up with the latest artificial intelligence technology, so our company will continue to upgrade the platform. **What problems is DataCanvas solving and how is that benefiting you?** DataCanvas enables developers and data scientists to quickly and efficiently build, train, and deploy machine learning models of any size, with rich feature analysis and presentation capabilities. ### 3. As a data science platform, DataCanvas is much easier to use than expected **Rating:** 5.0/5.0 stars **Reviewed by:** Zhenni W. | Marketing Specialist, Enterprise (> 1000 emp.) **Reviewed Date:** December 03, 2021 **What do you like best about DataCanvas?** Basically, there is no threshold limit for users. Second, it can realize end-to-end model construction. Third, it can also carry out the whole life cycle of the model. **What do you dislike about DataCanvas?** Although it supports three different modeling methods: coding, drag and drop and automatic modeling, the method used depends entirely on the user's technical ability. In the absence of data scientists today, perhaps it can provide some tutorials to help users learn more kinds of new modeling technologies. **What problems is DataCanvas solving and how is that benefiting you?** It enables me to manage models more clearly and methodically, including those under construction and those already built, which plays a good role in improving the efficiency of model use. ### 4. It made data analytics easier and faster **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Real Estate | Enterprise (> 1000 emp.) **Reviewed Date:** November 24, 2021 **What do you like best about DataCanvas?** The most useful function of DataCanvas is the AutoModeling part. Our operation team can use its built-in models to analyze industry data, customer data, etc., to support business decision-making more efficiently. The second reason that we chose it is that DataCanvas doesn't provide or storage users' data that fit the company's data security policy. **What do you dislike about DataCanvas?** Some of the built-in models are not applied to our industry and busines scenarios, hope they can rich them in the future. **What problems is DataCanvas solving and how is that benefiting you?** It helped our team members who could not code to complete data analysis works quickly with technical results. The best part is model results could also be stored and shared between all the team, which made the model property now considerable than we excepted. ### 5. Recommend DataCanvas as a great data science platform company. **Rating:** 5.0/5.0 stars **Reviewed by:** Yanxia L. | Enterprise (> 1000 emp.) **Reviewed Date:** January 11, 2021 **What do you like best about DataCanvas?** This company provide flexible, professional enterprise data science platform for end users. To lower the barrier of adopting machine learning, they also develop automl tools and open source this tool. During the past years, they have solid customer base and being broadly recommended by their customers. Founder & CEO of this company is very focused on data science software domain. Their employee are also very professional, dedicated and interesting. **What do you dislike about DataCanvas?** Their business strategy is not so aggressive, they spent all their efforts on the software product. As analyst, I think they should expand their voice and marketing activities under the current market environments. They should accelerate their market expansion. Sorry that do not have so many negations. **Recommendations to others considering DataCanvas:** If you are considering your company's enterprise AI strategy, you should consult DataCanvas. If you are going to build data science platform, you should ask DataCanvas for advice. They have great experience in this domain, and they can provide experienced data scientist for help. No matter you are engineer from enterprise, or developer/student from research institution, you can refer to DataCanvas for data science and ML developing. **What problems is DataCanvas solving and how is that benefiting you?** As analyst, I work with DataCanvas to interview their clients. From their clients, I learn that: DataCanvas emphasize to provide data science platform for both tech department and Lobs. They use big data analytics and machine learning for risk management business, product recommendation system, and quality investigation in manufacture. Their clients recommend DataCanvas because the platform is open, flexible and easy to use. ### 6. Accelerate to have autonomous AI capabilities **Rating:** 4.5/5.0 stars **Reviewed by:** Emma W. | Mid-Market (51-1000 emp.) **Reviewed Date:** January 11, 2021 **What do you like best about DataCanvas?** DataCanvas data science platform adopts open architecture, not bound to hardware and cloud services, fully supports mainstream technical architectures, and accommodates various computing architectures and modeling services. DataCanvas focuses on machine learning, automated modeling and model production, which can be quickly applied in scenarios to help companies automate their data science with many reputable practical cases. **What do you dislike about DataCanvas?** There's nothing I don't like. DataCanvas offers a rich set of products and tools that further lowers the bar for automated machine learning and enhances support for unstructured data in scenarios such as NLP. I would like to learn more about the latest technology and product details. **Recommendations to others considering DataCanvas:** Assess your own situation, including the need for a data science platform for each business scenario, the hardware and technical architecture, and the level of skills acquired by your employees. The DataCanvas data science platform is clearly positioned: an open, compatible, pure software platform. It provides a full range of autonomous AI capacity building, without relying on specific hardware or algorithm providers. **What problems is DataCanvas solving and how is that benefiting you?** Automate AI modeling and applications: Providing a one-stop machine learning platform, AutoML lowers the threshold for modeling and makes it accessible to many business units. When AI capabilities are insufficient, the platform's built-in algorithms can be used directly.DataCanvas provides a viewable and customizable "white-box" algorithm library to flexibly meet the enterprise AI construction autonomy and control. ### 7. Top ML Platform **Rating:** 5.0/5.0 stars **Reviewed by:** Cheng Y. | Partner, Small-Business (50 or fewer emp.) **Reviewed Date:** March 17, 2021 **What do you like best about DataCanvas?** The user interface is intuitive, it takes little training to get my staff up to speed; I also like its programmability, which allows the team to see and edit the model any time they wish **What do you dislike about DataCanvas?** I can use more industry oriented templates **What problems is DataCanvas solving and how is that benefiting you?** We run business analysis on the latest market info. The work is agile and the goals are constantly changing. So we need a fluid way to build models. Data Canvas seems to do the trick so far. ### 8. Datacanvas's not a seller, it's a good friend who wishes to grow together with their customers. **Rating:** 5.0/5.0 stars **Reviewed by:** xu f. | Small-Business (50 or fewer emp.) **Reviewed Date:** January 02, 2021 **What do you like best about DataCanvas?** Datacanvas is technology and innovation oriented. **What do you dislike about DataCanvas?** Sometimes we need its core person's suppoert from headquarter (BEIJING), it costs a little bit more time. **What problems is DataCanvas solving and how is that benefiting you?** We are cooperating a big data project. They consider customer's satisfiction is the most important thing. ### 9. AI is the future **Rating:** 5.0/5.0 stars **Reviewed by:** shan q. | Enterprise (> 1000 emp.) **Reviewed Date:** December 23, 2020 **What do you like best about DataCanvas?** The product is easy to use, realizing the whole life cycle management of the model. **What do you dislike about DataCanvas?** There's nothing I don't like............ **What problems is DataCanvas solving and how is that benefiting you?** AI quality inspection and inspection. Downsizing and efficiency improvement. ### 10. I am a traditional software developer, but through DataCanvas, I can also work on artificial intelligence. With automated modeling, drag-and-drop modeling, and rich algorithm support, even those who don't understand algorithms can quickly get started. **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Electrical/Electronic Manufacturing | Enterprise (> 1000 emp.) **Reviewed Date:** December 28, 2020 **What do you like best about DataCanvas?** 1. Trinity modeling. 2. Automatic modeling, drag and drop, and code implementation are interchangeable, allowing for flexibility and adaptation to different users. **What do you dislike about DataCanvas?** From the current usage perspective, the entire platform is a complete closed loop, from data access, data analysis, modeling, training, to deployment and inference, forming a full-process closed loop. Therefore, all stages are indispensable. The design is very complete, with no obvious flaws. **Recommendations to others considering DataCanvas:** We hope that this product can continue to be optimized and upgraded, keeping up with the latest artificial intelligence technology, so that our company can also continuously upgrade the platform. **What problems is DataCanvas solving and how is that benefiting you?** Solved tasks related to machine vision, natural language, data analysis, and mining. This platform has resolved a large amount of tedious configuration work, greatly improving work efficiency. ## DataCanvas Discussions - [What is DataCanvas used for?](https://www.g2.com/discussions/what-is-datacanvas-used-for) - [Before using DataCanvas, what were you using?](https://www.g2.com/discussions/35774-before-using-datacanvas-what-were-you-using) - 1 upvote - [View DataCanvas pricing details and edition comparison](https://www.g2.com/products/datacanvas/reviews?section=pricing&secure%5Bexpires_at%5D=2026-06-30+10%3A21%3A16+-0500&secure%5Bsession_id%5D=5481e050-2986-4df1-84b1-11427a4d3a13&secure%5Btoken%5D=0ee1f65b5944971d63102b1bf1b1ab4b2d15fa3efa39abfaee10242094497450&format=llm_user) ## DataCanvas Features **System** - Data Ingestion & Wrangling **Model Development** - Language Support - Drag and Drop - Pre-Built Algorithms - Model Training **Model Development** - Feature Engineering **Machine/Deep Learning Services** - Computer Vision - Natural Language Processing - Natural Language Generation - Artificial Neural Networks **Machine/Deep Learning Services** - Natural Language Understanding - Deep Learning **Deployment** - Managed Service - Application - Scalability **Generative AI** - AI Text Generation - AI Text Summarization - AI Text-to-Image **Agentic AI - Data Science and Machine Learning Platforms** - Autonomous Task Execution - Multi-step Planning - Cross-system Integration - Adaptive Learning - Natural Language Interaction - Proactive Assistance - Decision Making ## Top DataCanvas Alternatives - [Databricks](https://www.g2.com/products/databricks/reviews) - 4.6/5.0 (1,284 reviews) - [Deepnote](https://www.g2.com/products/deepnote/reviews) - 4.5/5.0 (377 reviews) - [Domo](https://www.g2.com/products/domo/reviews) - 4.3/5.0 (996 reviews)