Achieving data scalability
One of the main problems of traditional architectures based on relational databases and the data warehouse is that these solutions do not scale well compared to the explosive growth of data. Such architectures need to be adequately sized, even in the design phase.
With the spread of big data analytics, it was, therefore, necessary to move on to other paradigms for data storage, known as distributed storage systems, which allow for the precise prevention of bottlenecks in the management and storage of data.
Cloud computing makes extensive use of such distributed storage systems to enable the analysis of large amounts of data (big data analytics), even in streaming mode.
Distributed storage systems consist of non-relational ...
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