Simplifying and Future-Proofing Hadoop
Customers are asking how to choose from the rich and growing array of tools in the Hadoop ecosystem. Part of the consideration centers on how to insulate them from fragmentation in the continually evolving Hadoop ecosystem. The incredibly rapid pace of innovation distinguishes the ecosystem but it also has its downsides. The mix and match richness of choice introduces complexity for administrators and developers.
At some point it makes sense for customers to consider investing in tools that can hide much of that complexity in data ready for analysis. To be clear, there is no magic product that can hide all these technologies. But when customers take the perspective of simplifying specific end-to-end processes, solutions are available to address the problem.
Making Sense of Hortonworks’ Dataflow
IT leaders can no longer treat stream processors as esoteric functionality employed solely by leading-edge consumer Internet services. They are becoming core functionality that works side-by-side with the more familiar batch processing engines such as Hive, HBase, or Impala. Application developers that need near real-time functionality can start to evaluate stream processors as part of design patterns. However, their analytics functionality is still a bit primitive and most of them need a lot of hardening in order to be resilient enough for mainstream customers.
Making Sense of Hortonworks' Dataflow
IT leaders can no longer treat stream processors as esoteric functionality employed solely by leading-edge consumer Internet services. They are becoming core functionality that works side-by-side with the more familiar batch processing engines such as Hive, HBase, or Impala. Application developers that need near real-time functionality can start to evaluate stream processors as part of design patterns. However, their analytics functionality is still a bit primitive and most of them need a lot of hardening in order to be resilient enough for mainstream customers.
Unpacking the Public Cloud Market
Wikibon Research has forecasted Public Cloud revenues from 2015 through 2026; with the expectations that 33% of all IT spending ($500B) will move to Public Cloud services within the next decade. The impact this will have on IT vendors and IT strategy will be significant as more applications focus on mobile and real-time data analytics.
Server SAN 2012-2026
In this research paper, Wikibon looks back at the introductory Server SAN research, adjusts the Server SAN definition to include System Drag, and increases the speed of adoption of Server SAN based on very fast adoption from 2012 to 2014. The overall growth of Server SAN is projected to be about a 23% CAGR from 2014 to 2026, with a faster growth from 2014 to 2020 of 38%. The total Server SAN market is projected to grow to over $48 billion by 2026. The traditional enterprise storage market is projected to decline by -16% CAGR, leading to an overall growth in storage spend of 3% CAGR through 2026. Traditional enterprise storage is being squeezed in a vice between a superior, lower cost and more flexible storage model with Enterprise Server SAN, and the migration of IT towards cloud computing and Hyperscale Server SAN deployments. Wikibon strongly recommends that CTOs & CIOs initiate Server SAN pilot projects in 2015, particularly for applications where either low cost or high performance is required.
Systems of Intelligence Part 2: Foundation Platform
Mainstream IT, LoB execs and application development professionals each provide different yet critical perspectives to Systems of Intelligence. IT exes must be in a position to deliver the right infrastructure (e.g. cloud, on-prem, etc.) with the proper performance and SLA profile to support LoB requirements. Line-of-Business execs must have enough knowledge to specify the real-time needs of applications while application development pros must ensure the right skills are in place to deliver and maintain services to Systems of Intelligence over a full life cycle.
Big Data Vendor Revenue and Market Forecast, 2011-2026
The Big Data market continued its maturation in 2014, experiencing both significant growth as measured by vendor revenue and increased adoption of Big Data tools and technologies by large enterprises across vertical markets. In this exclusive report for Wikibon Premium members, Wikibon details Big Data vendor revenue and extends its groundbreaking market forecast through 2020.
The Next Phase of Converged Infrastructure
Converged infrastructure is a trend that has been growing for over 5 years and is rapidly transforming the way that users consume IT. In 2012, Wikibon forecasted (see Converged Infrastructure Takes the Market By Storm) that 2/3 of infrastructure for enterprise applications would be packaged as some form of converged infrastructure by 2017. Now there […]
Breaking Down the Hortonworks S-1
Hortonworks plans to go public in 2015 and its S-1 filing, revealed to the world yesterday, says a lot about the state of the Hadoop market generally and, obviously, Hortonworks specifically. First, a mea culpa. In Wikibon’s latest Big Data market forecast, my colleagues and I provided our estimate for Hortonworks’ 2013 revenue (along with revenue estimates […]