BigDataFr recommends: Real-time, not batch-time, analytics with Hadoop
How big data, fast data, and real-time analytics work together in the real world.
‘Today, we often hear the phrase “The 3 Vs” in relation to big data: Volume, Variety and Velocity. With the interest and popularity of big data frameworks such as Hadoop, the focus has mostly centered on volume and data at rest. Common requirements here would be data ingestion, batch processing, and distributed queries. These are well understood. Increasingly, however, there is a need to manage and process data as it arrives, in real time. There may be great value in the immediacy of that data and the ability to act upon it very quickly. This is velocity and data in motion, also known as “fast data.” Fast data has become increasingly important within the past few years due to the growth in endpoints that now stream data in real time.
Big data + fast data is a powerful combination. However, adding real-time analytics to this mix provides the business value. Let’s look at a real example, originally described by Scott Jarr of VoltDB.’
About Akmal Chaudhri
Akmal B. Chaudhri is an Independent Consultant, specializing in Big Data, NoSQL and NewSQL database technologies. He has previously held roles as a developer, consultant, product strategist and technical trainer with several Blue-Chip companies and Big Data startups.