Storage and Big Data

Efficiently extracting relevant information from massive quantities of collected data is increasingly a key requirement for keeping your business ahead of the competition. Formerly, speaking SQL was the way of performing data retrieval. However, there are today numerous technologies ranging from full text search, to object stores and key-value tables. Big data requires new programming paradigms and blurs the boundaries between databases and file systems. Track participants learn about the advantages and pitfalls of storage engines, NoSQL databases, and search indices. A list of tools and projects might include but is not limited to MongoDB, Elastic Search, Redis, Hadoop, Cassandra, Swift, Ceph, Solr, Lucene, Map Reduce, HDFS, and Hadoop.