MATLAB vs SAP HANA

MATLAB is a computing and programming tool that combines the power of functions and algorithms with data integration, modeling and visualization for predictive business data analysis. Users perform complex computations on data sets that the platform ingests from a multitude of data sources to glean business-specific metrics. Citing online communities, all users who reviewed support said that the tool is accessible to beginners, while providing enough depth for advanced users, though some said that the coding syntax could be daunting for non-technical users initially. Around 92% of users who reviewed its analytical capabilities said that the platform provides a wide range of built-in packages to provide out-of-the-box data analysis solutions. With its minimal scripting, many users who discussed data processing said that they could simulate complex mathematical functions to visualize complex data models. Reviewing its functionality, many users said that its rich library and design makes it possible to write powerful programs easily. A majority of users who discussed its performance said that the platform consumes a lot of power and space and slows down when performing complex computations, possibly because updates, though frequent, do not include optimization for older features. Many users who reviewed the cost said that individual user licenses are expensive, and buying additional libraries adds to the cost since many of these have interlinking dependencies, though some users said that the platform provides value for money. In summary, MATLAB is a programming solution that leverages machine learning for data collection and complex computations for users to create data models and visualize enterprise metrics for predictive analysis.

SAP HANA is a multi-model database and analytics platform that combines real-time transactional data with predictive analytics and machine learning capabilities to drive business decisions quicker. Most of the users who mentioned analytics said that, with its Online Analytical Processing(OLAP) and Online Transactional Processing(OLTP) capabilities, the tool analyzes data faster with predictive modeling and machine learning. Many users who reviewed data processing said that the tool has a lean data model due to its in-memory architecture and columnar storage capabilities, and, paired with its compression algorithm, can perform calculations on-the-fly on huge volumes of data. In reference to data integration, many users said that the platform connects seamlessly with both SAP and non-SAP systems, such as mapping tools like ArcGIS, to migrate data to a consolidated repository, though quite a few users said that integration with media files and Google APIs is tedious. Most of the users who reviewed support said that they are responsive, and online user communities and documentation help in resolving issues, whereas some users said that the support reps had limited knowledge. A majority of the users who reviewed its speed said that the platform has a fast runtime, though some users said that it requires high-performing hardware infrastructure to do so and that memory management might be tricky with large datasets. The software does have its limitations though. Being in-memory, the tool is RAM-intensive, which can add to the cost of ownership, though some users said that data compression reduces the database size and saves on hardware cost. A majority of the users who reviewed its functionality said that it needs to be more mature in terms of flexibility and agility, though some users said that with easy updates and maintenance, it is a robust solution and increases efficiency and productivity. In summary, SAP HANA serves as a single source of truth for analysis of large volumes of data and uncovering consumer insights through planning, forecasting and drill-down reporting. However, it seems more suited for large organizations with complex data types and analytics workflows because of its costly pricing plans.