# Ganitha Reviews **Vendor:** Tresata **Category:** [Machine Learning Software](https://www.g2.com/categories/machine-learning) **Average Rating:** 4.3/5.0 **Total Reviews:** 11 ## About Ganitha Ganitha is an open-source library (derived from the Sanskrit word for mathematics, or science of computation) is a Scalding library with a focus on machine-learning and statistical analysis. ## Ganitha Pros & Cons **What users like:** - Users value Ganitha for its **efficiency in handling large data volumes** , simplifying complex data tasks significantly. (4 reviews) - Users appreciate the **user-friendly interface** of Ganitha, making complex data handling accessible and efficient for all. (4 reviews) - Users value the **wide model variety** of Ganitha, enhancing their ability to tackle diverse data challenges efficiently. (4 reviews) - Users value the **seamless integrations** of Ganitha with various tools, enhancing data processing efficiency and flexibility. (3 reviews) - Users value the **flexibility** of Ganitha, enabling efficient handling of large data volumes and complex analyses. (2 reviews) - Intuitive (2 reviews) - Machine Learning (2 reviews) - Navigation Ease (2 reviews) - AI Technology (1 reviews) - Customization Options (1 reviews) **What users dislike:** - Users find the **poor documentation** of Ganitha frustrating, as it lacks practical examples and clear guides. (3 reviews) - Users find **difficult learning** curves with Ganitha, struggling to utilize its full capabilities effectively, especially newcomers. (2 reviews) - Users find the **learning curve steep** for Ganitha, especially those new to Scalding, hindering full usage of its features. (1 reviews) - Users find Ganitha has **limited customization** , which may not meet the needs of advanced users seeking deeper analysis. (1 reviews) - Users feel that Ganitha has **limited features** for advanced analysis and lacks comprehensive documentation for support. (1 reviews) - Slow Performance (1 reviews) ## Ganitha Reviews ### 1. Powerful Machine Learning & Statistical Analysis tool for the Complex Relationships in COMPUTATION **Rating:** 4.0/5.0 stars **Reviewed by:** Mohammad M. | Senior Manager - PMO, Information Technology and Services, Small-Business (50 or fewer emp.) **Reviewed Date:** March 07, 2024 **What do you like best about Ganitha?** Ganitha makes large-scale machine learning and statistical analysis seamless. Its integration with Hadoop and Scalding allows us to process massive datasets efficiently, while built-in algorithms like K-means|| deliver excellent performance for clustering. **What do you dislike about Ganitha?** Ganitha has a steep learning curve, especially for users unfamiliar with Scalding or the Hadoop ecosystem. The documentation could be more detailed, with additional examples and tutorials to make onboarding easier. **What problems is Ganitha solving and how is that benefiting you?** Streamline of complex data which ends up in resolving our daily requirement. ### 2. powerful for statistical analysis and machine learning **Rating:** 4.0/5.0 stars **Reviewed by:** Jimmy W. | Executive Producer , Mid-Market (51-1000 emp.) **Reviewed Date:** October 21, 2024 **What do you like best about Ganitha?** It makes handling large volumes of data efficient and relatively straightforward. The ability to perform complex data manipulation and transformation operations in big data workflows has been crucial in my work. The library offers a wide range of machine learning algorithms, from simple regressions to more complex models such as decision trees and neural networks. It can also integrate with other libraries and analysis tools, such as Apache Spark and Hadoop, has allowed for a flexible and robust working environment. **What do you dislike about Ganitha?** For new users, especially those unfamiliar with Scalding, it can take time to fully understand how to take full advantage of Ganitha's capabilities. **What problems is Ganitha solving and how is that benefiting you?** Using Ganitha has brought several significant benefits to my projects. First, the ability to handle large data sets and perform complex analytics has improved the efficiency of my workflows. I have been able to develop accurate predictive models and perform detailed statistical analysis without having to switch platforms. ### 3. My Personal Experience with a Powerful Analysis Tool **Rating:** 3.5/5.0 stars **Reviewed by:** Giedre M. | Head of Creative Operations , Mid-Market (51-1000 emp.) **Reviewed Date:** October 16, 2024 **What do you like best about Ganitha?** I was impressed with its seamless integration with Scalding and its focus on statistical analysis. The ease with which I was able to perform complex data processing tasks and build machine learning models saved me a significant amount of time. Ganitha offers a wide range of tools and functionalities that simplify working with large volumes of data, something that had always been a challenge in my previous projects. **What do you dislike about Ganitha?** Initially, I had difficulty understanding how to take full advantage of its capabilities. In addition, the documentation, while comprehensive, could benefit from more practical examples and detailed tutorials to help new users get started more quickly. **What problems is Ganitha solving and how is that benefiting you?** Thanks to its powerful analytics algorithms and machine learning models, I have been able to get more accurate and valuable insights from my data. This has not only improved the quality of my analysis, but also significantly increased the efficiency of my workflow. In addition, the fact that it is an open source tool gives me the freedom to customize and adapt the library to my specific needs, something I consider a big plus. ### 4. Simplicity and Usabilty in Mathematical Data Management **Rating:** 4.5/5.0 stars **Reviewed by:** Mark P. | Creative, Mid-Market (51-1000 emp.) **Reviewed Date:** October 09, 2024 **What do you like best about Ganitha?** I have been using Ganitha to manage calculations and mathematical data on some recent projects, not only is it intuitive, but it puts all the essentials at my fingertips, without unnecessary complications. Right out of the box, the platform feels light and straightforward, perfect for those looking for a fast and efficient solution to handle large amounts of data or perform complex calculations without having to deal with cluttered interfaces. **What do you dislike about Ganitha?** Simplicity and Usability in Mathematical Data Managemen Ganitha may fall short in terms of more advanced features or customizations. For more experienced users looking for deeper analysis or integration options, it may feel limited. Also, documentation is somewhat sparse, which has sometimes led me to do some research on my own or try various routes to solve a specific problem. **What problems is Ganitha solving and how is that benefiting you?** Ganitha is ideal for companies or professionals who need an agile tool with no learning curve to manage mathematical calculations without the excess functionality of more complex software. ### 5. A powerful tool **Rating:** 4.5/5.0 stars **Reviewed by:** Gustavo D. | Executive Creative Director, Mid-Market (51-1000 emp.) **Reviewed Date:** October 14, 2024 **What do you like best about Ganitha?** offers great flexibility and a wide range of functionalities for statistical analysis and machine learning. The integration with Scalding allows handling large volumes of data efficiently, which is essential for commercial projects that handlebig data. **What do you dislike about Ganitha?** One of the main drawbacks of Ganitha is its lack of documentation and practical examples. Although powerful, the lack of clear guides and detailed tutorials can be frustrating. **What problems is Ganitha solving and how is that benefiting you?** Its ability to handle and analyse large data sets allows businesses to perform deep and accurate analysis, which is essential for informed decision making. In addition, integration with Scalding facilitates large-scale data processing, which is crucial in industries such as finance, marketing and scientific research. ### 6. **Machine Learning Potential** **Rating:** 4.0/5.0 stars **Reviewed by:** Pierre V. | Studio Coordinator, Mid-Market (51-1000 emp.) **Reviewed Date:** October 09, 2024 **What do you like best about Ganitha?** What really makes Ganitha stand out is its usability. As a Scalding library, it allows users to integrate data from multiple sources and perform complex analysis without a steep learning curve. The interface is accessible and well-designed, making it easy to navigate even for those who are not programming experts. This is especially useful in business environments where speed of decision making is crucial. **What do you dislike about Ganitha?** I have faced significant challenges. Slow data processing can be frustrating, especially when working with large data sets. **What problems is Ganitha solving and how is that benefiting you?** Ganitha offers great potential in the area of machine learning and statistical analysis, standing out for its usability. ### 7. Helpful in managing uncommon inquiry dilemmas. **Rating:** 4.5/5.0 stars **Reviewed by:** Ghulam M. | Senior Sales Strategist, Construction, Mid-Market (51-1000 emp.) **Reviewed Date:** October 02, 2024 **What do you like best about Ganitha?** In my data science role tackling challenging machine learning solutions I see great importance in the statistical focus of Ganitha alongside its connection with Scalding. Open-source enables extensive customization and the investigation of algorithms. **What do you dislike about Ganitha?** Ganitha needs to develop a rich set of machine learning functions that are already built. I regularly put in a great deal of effort and time to build common algorithms without pre-built solutions. **What problems is Ganitha solving and how is that benefiting you?** Ganitha solves the difficulties of handling vast datasets for machine learning activities through integration with Scalding from Apache Hadoop. Handling complicated data sets becomes simpler while I carry out laborious calculations. ### 8. reviewing an open source lib **Rating:** 5.0/5.0 stars **Reviewed by:** Somdeb K. | Financial Analyst, Small-Business (50 or fewer emp.) **Reviewed Date:** May 08, 2024 **What do you like best about Ganitha?** so many mathematical packages at once in one go.. **What do you dislike about Ganitha?** it lags a bit in mac os.. but runs smooth on windowds any version... **What problems is Ganitha solving and how is that benefiting you?** multiple mathematical packages in different languages ### 9. Really Gooood!! **Rating:** 4.0/5.0 stars **Reviewed by:** Rishab J. | Manager - Finance & Accounts, Mid-Market (51-1000 emp.) **Reviewed Date:** November 22, 2023 **What do you like best about Ganitha?** Makes computing easy. Helps in getting the job done with my employees at a faster rate. **What do you dislike about Ganitha?** There's not much to be dissatisfied about. **What problems is Ganitha solving and how is that benefiting you?** Streamlining of data has helped our productivity multifold. ### 10. Excellent awesome **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Market Research | Small-Business (50 or fewer emp.) **Reviewed Date:** August 05, 2023 **What do you like best about Ganitha?** Amazing calculation system; I appreciate how it makes it simple to interact with my staff and complete tasks **What do you dislike about Ganitha?** We wish that there were more applications, but overall I'm extremely satisfied. **What problems is Ganitha solving and how is that benefiting you?** I'm working with my business to resolve my data collection problems. ### 11. Amazing! Amazing! **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Mid-Market (51-1000 emp.) **Reviewed Date:** June 12, 2018 **What do you like best about Ganitha?** Amazing computation system, i love how it’s easy to communicate with my employees, and can get the task done **What do you dislike about Ganitha?** I wish it had more uses, but over all satisfaction is very good. **What problems is Ganitha solving and how is that benefiting you?** I am solving my statistical issues within my company. ## Ganitha Discussions - [What is Ganitha used for?](https://www.g2.com/discussions/what-is-ganitha-used-for) - 1 comment - [View Ganitha pricing details and edition comparison](https://www.g2.com/products/ganitha/reviews?section=pricing&secure%5Bexpires_at%5D=2026-05-18+21%3A43%3A59+-0500&secure%5Bsession_id%5D=a230ea09-2d37-4776-a97a-46900310babd&secure%5Btoken%5D=50aa413ec5f005237e248671bfe37fd1a16fcbb79905a7bfa97a431eb5009040&format=llm_user) ## Ganitha Features **Integration - Machine Learning** - Integration **Learning - Machine Learning** - Training Data - Actionable Insights - Algorithm ## Top Ganitha Alternatives - [Automation Anywhere Agentic Process Automation](https://www.g2.com/products/automation-anywhere-agentic-process-automation/reviews) - 4.5/5.0 (4,009 reviews) - [Demandbase One](https://www.g2.com/products/demandbase-one/reviews) - 4.4/5.0 (1,893 reviews) - [Phrase Localization Platform](https://www.g2.com/products/phrase-localization-platform/reviews) - 4.5/5.0 (1,261 reviews)