There is a plethora of storage solutions for big data, each having its own pros and cons. The objective of this talk is to delve deeper into specific classes of storage types like Distributed File Systems, in-memory Key Value Stores, Big Table Stores and provide insights on how to choose the right storage solution for a specific class of problems. For instance, running large analytic workloads, iterative machine learning algorithms, and real time analytics.
The talk will cover HDFS, HBase and brief introduction to Redis
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