Similarly, MapR missed a self-imposed deadline of 3 July to secure new funding or attract a buyout, leaving the company at risk of staff layoffs and closure of its headquarters. The Hadoop distribution vendors are seeing the effects of this now, with Hortonworks being consumed by Cloudera, who have since reported challenges in maintaining business growth. Shifting from capital hardware depreciation to operational expenditure for cloud becomes straightforward. The significant capital investments companies made to build out data centers to host their Hadoop data and workloads have just now moved past the typical 2 to 4-year depreciation period, allowing those costs to be written off now.
The level of interest in Hadoop peaked in June 2015, and has been declining ever since. The economic advantages of the cloud for new big data systems are clear, but there is also a key reason why it is the right time now for organizations to make the shift to the cloud. Hardware maturity cycle signals the right time for big data to move to the cloud Big data has found a natural home in the cloud, and organizations are tasked with taking advantage of it.
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The accelerating consolidation of and diminishing opportunities for Hadoop vendors is directly related to the increasing use of cloud-native systems for storing and processing big data, where you can take full advantage of cheap, scalable storage and the flexibility that comes from the capacity and breadth of analytic platforms there. When deciding where new capabilities will be developed and operate, the cloud is now the first choice for most enterprises. The rise of the cloud has seen the most fundamental shift in IT in many decades. Migrating Big Data to the Cloud with WANdisco LiveMigrator, ADLS Gen2, Databricks and Delta Lake
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