As data continues to grow in both volume and structural variety, traditional relational database approaches fall increasingly short in providing the needed flexibility, agility, scalability, and economy to support its processing. Alternative and complimentary approaches for managing information have been pioneered, and given time to mature, in the last few years to satisfy today’s big data storage and processing needs. Most prominent among them for centrally managing the onslaught of all the information a business needs to process and store are Data Lakes.
What is the purpose of a Data Lake?
Data Lakes offer a far more economic and imminently scalable approach for ingesting and assimilating an ever changing range of input data primarily because they can be implemented on top of the open source Hadoop eco system. Hadoop provides an architecture that can scale as needed by simply adding commodity servers to the cluster for increased parallel processing and storage. Due to […]