If the use case involves creating a data warehousing solution with complex functionality, data analytics, and extensive querying requirements, especially if there's a need for a data lake, then opting for Hadoop and Spark is advisable. In this scenario, Hadoop with technologies like Hive and Spark can provide the necessary capabilities. On the other hand, if the application's primary focus is on handling large volumes of data without the requirement for complex features, data warehousing, or advanced querying, and if dashboarding visibility is not a priority, then MongoDB could be a suitable choice. Overall, I would rate it nine out of ten.
Project Management Software facilitates task organization and resource management, enhancing collaboration and productivity across teams.With various solutions available, these systems offer integrations with third-party tools, customizable dashboards, and comprehensive reporting features. They cater to different industries, adapting to specific requirements while streamlining processes.What key features should you consider?
Task Management: Organizes tasks for efficient workflow.
Resource...
If the use case involves creating a data warehousing solution with complex functionality, data analytics, and extensive querying requirements, especially if there's a need for a data lake, then opting for Hadoop and Spark is advisable. In this scenario, Hadoop with technologies like Hive and Spark can provide the necessary capabilities. On the other hand, if the application's primary focus is on handling large volumes of data without the requirement for complex features, data warehousing, or advanced querying, and if dashboarding visibility is not a priority, then MongoDB could be a suitable choice. Overall, I would rate it nine out of ten.