Data & AI

“Thru 2018, 70 percent of Hadoop deployments will not meet cost savings and revenue generation objectives due to skills and integration challenges.”  – Nick Heudecker, Gartner Analyst A Gartner research report on Apache Hadoop found that 46 percent of companies surveyed plan Hadoop investments, marking a slow but steady adoption. However, there are still questions […]

If you’re heading to Dreamforce 2015, proper planning, figuring out what you want to do and where you want to go are essential to avoid wasting time.

By now you may have heard that Apache Spark is the fastest growing project in open source ‘Big Data’ community. Spark does not include its own distributed data persistence technology but can work with any Hadoop-compatible data formats. You can use the MarkLogic Connector for Hadoop as an input source to Spark and take advantage of the Spark framework to develop your ‘Big Data’ applications on top of MarkLogic.

Rebalancing in MarkLogic redistributes content in a database so that the forests that make up the database each have a similar number of documents. Spreading documents evenly across forests lets you take better advantage of concurrency among hosts.