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Because of the massive utilization of the world wide web and the drastic use of electronic gadgets to access the online world, there is an exponential growth in the information produced by these hardware gadgets. The data produced by different sources, such as smart transportation, healthcare, and e-commerce, are large, complex, and heterogeneous. Therefore, storing and querying this data, coined "Big Data," is challenging. This paper compares relational databases with a few of the popular NoSQL databases. The performance of various databases in executing join queries, filter queries, and aggregate queries on large datasets are compared on a single node and multinode clusters. The experimental results demonstrate the suitability of NoSQL databases for Big Data Analytics and for supporting large userbase interactive web applications.

A development of an orchestrator that manages multiusers and shared resources is extremely useful for automaton of jobs on the multiple machines. Many companies such as UiPath, Blue Prism, Automation Anywhere, etc. have their own orchestrator, but their orchestration services have some drawbacks (i.e., huge cost of yearly subscription, lack of user defined flexibility in architecture, and third-party security issues). The manuscript contains the design and analysis of orchestrator using open-source programming language and cloud platform (i.e., Python and OpenStack). The main focus of this paper is design and development of the orchestrator with shared resources and distribute environment management system that help to manage the multiuser, multi-machine environment in an efficient way. The overall examination delights that design and development of inhouse orchestrator application using open-source assets is not only useful in terms of colossal expense slicing, but also the development of free and flexible robotic process automation applications.