Much of the focus on real-time big data has been on the capture and processing of real-time unstructured data from machines, sensors, web pages, and other Internet of Things (IoT) sources, but for a ...

Integrating distributed, in-memory computing with distributed caching can easily extend LINQ semantics to create important new capabilities for real-time analytics on fast-changing data. In the age of ...

Facebook yesterday open sourced Presto, its distributed SQL query engine built to improve Big Data analytics beyond existing solutions such as Hadoop MapReduce and Hive. The improvements are ...

Hadoop is a notoriously difficult system on which to run interactive queries. JethroData developed a SQL-on-Hadoop engine that acts as a business intelligence-on-Hadoop acceleration layer that speeds ...

The new Amazon Athena tool from Amazon Web Services Inc.(AWS) enables serverless queries of large amounts of data stored in Amazon Simple Storage Service (Amazon S3), obviating the need to spin up ...

SAN MATEO, Calif., April 6, 2017 /PRNewswire/ -- AtScale, the first company to provide enterprises with a fast and secure self-service Business Intelligence platform for Big Data, released today the ...

Google wants to make all blockchain data associated with Ethereum easily accessible for people to study. It’s doing that by making all Ethereum data sets available through BigQuery, Google’s ...

Big Data is supposed to level the business playing field, but up until now it has not. Because even though it’s cheaper to store data in Hadoop or to work with open source NoSQL in theory, it’s too ...

One of the most conspicuous examples of big data in action is Google’s data-aggregating tool Google Flu Trends (GFT). The ...

Forbes contributors publish independent expert analyses and insights. I write about the broad intersection of data and society. In an era where almost everything is touted as being “big data” how do ...