In an earlier blog post, I discussed some architectural options in deploying a big data environment, including cloud vs. on-premises, and dedicated vs. shared infrastructure. In this post, I'll examine topics that may be even more divisive: open vs. proprietary software and commodity vs. purpose-built hardware. These choices seem to reflect personal philosophies as much as technological differences.
At a recent Analyst Day in San Francisco, Cloudera all but declared the company’s dominance of the core Hadoop distribution market. The case was made around three measures of success, namely: product strength, market results, and strategic alliances.
At a recent Analyst Day in San Francisco, Cloudera all but declared the company’s dominance of the core Hadoop distribution market. The case was made around three measures of success, namely:
When I was in college, my housemate Craig* justified his lack of tidiness with a theory he espoused as the "One Pile Method." In practice, this involved dumping all of his clothes, books, homework, sports equipment, and anything else he happened to be carrying right in the middle of his room upon entry. The argument was that anytime he needed anything, he knew right where to look—it had to be somewhere in that one pile. This was claimed to be highly efficient in terms of time and efforts.
The recent Strata + Hadoop World show in San Jose was again a fascinating cross-section of the larger big data and analytics market space. Watch our "man on the scene" video or read on below for some quick highlights. Note: the one-side flared collar is a fashion fad you saw here first!
The content delivery network (CDN) market largely appears to be a mature market that is dominated by Akamai due to the market’s apparent affinity for a high degree of physical network infrastructure and caching to minimize the impact of last mile issues. It’s therefore surprising to see the degree of attention focused on Instart Logic by some of Silicon Valley’s leading entrepreneurs and VCs. Instart Logic is a west coast application delivery startup with funding from Andreessen Horowitz, Greylock Partners, Kleiner Perkins Caufield & Byers, Sutter Hill Ventures, Tenaya Capital, and several notable Silicon Valley angel investors. This is the A-team when it comes to investors and a group whose attention is not easy to attract.
In order to assess IT spending priorities over the next 12-18 months, ESG recently surveyed 601 IT professionals representing midmarket (100 to 999 employees) and enterprise-class (1,000 employees or more) organizations in North America and Western Europe. All respondents were personally responsible for or familiar with their organizations’ 2014 IT spending as well as their 2015 IT budget and spending plans at either an entire organization level or at a business unit/division/branch level.
I'm a "big data" guy, in the broadest, most aggressively futuristic sense of the term. So when Tom Davenport opened the TDWI keynote saying he doesn't like the Kardashians and he doesn't like the term "big data," I was alarmed. Was this going to be another grandpa-style lecture on how business intelligence and data warehousing didn't need any of them new-fangled gizmos? You know the spiel, "Back in my day we did analytics on the way to school, for 10 miles, uphill both ways, in the snow, without shoes, and we were happy to do it!" When he started on his history of decision support analytics, I began to wonder if there there any earlier flights available out of Las Vegas that day....
In my first post of this blog series on big data deployment models, I discussed some of the fundamental choices enterprises must make and shared a somewhat tongue-in-cheek flowchart to help people think about their options on how to host a new big data environment.
Optimization is surfacing more frequently in the applications and tools markets. I was recently speaking with a vendor who competes in the content delivery network (CDN) market about their optimization technology. Consequently, I started thinking about optimization, its role in decision analytics, and how it is applied.
This report examines Quantum’s DXi6900 deduplication disk backup appliance, powered by Quantum’s StorNext 5 data management technology, with a focus on how the DXi6900 fits into Quantum's broad and deep data protection portfolio. ESG Lab examined the performance, deduplication, replication, data availability, scalability, and encryption capabilities of the DXi6900. Additional testing included virtual machine backup and archiving with Quantum’s vmPRO, disaster recovery solutions with Quantum’s Scalar tape libraries and Q-Cloud services, management with Quantum Vision software, and integration with independent software vendor (ISV) offerings such as Symantec's NetBackup OpenStorage (OST) and Auto Image Replication (AIR).
At the start of the year, about 6 weeks way back, I made a number of predictions about the big data, business intelligence, and analytics market. See my previous posts here, here, and here. While it may seem early to measure the results for the current year, from this collection of recent vendor announcements it sure looks like the accuracy will be proven out!
ESG Founder and Senior Analyst Steve Duplessie interviews Senior Analyst Nik Rouda on his 2015 predictions for the Data Management segment.
In addition to announcing record revenues and profits, Apple’s recent Q1 2015 earnings call included an update on the firm’s mobile app development and analytics partnership with IBM. New ESG research finds that the alliance is resonating with customers: A considerable 30% of enterprise organizations say that the partnership will significantly accelerate their use of iOS devices and applications. This is especially true in key industry verticals (and traditional Big Blue bulwarks) highlighted by Apple CEO Tim Cook as the focus of initial app delivery, including retail and financial services.
I get asked all the time about the "best" option for deploying big data. Most people are curious about the impact of choices between...
Long-time collaborators IBM and Cisco recently introduced a new converged infrastructure solution, VersaStack. Available through IBM and Cisco’s qualified business partners, this new solution focuses on making cloud, big data and analytics, and mobile deployments attainable and efficiently packaged for simplified deployment. This solution gives IBM and Cisco a unique advantage in the integrated full-stack market, as long as it can demonstrate the value of the B Series Blade Servers coupled to the strategic direction Cisco is headed in with ACI architectures, and Cisco Intercloud Fabric with IBM’s enterprise accounts.
Ok, I admit that examining the US Federal government's budget doesn't sound exciting. Unless you are a politics junkie, looking for a sound bite to get outraged around, no one wants to pore through a big spreadsheet of long line items. We pay our taxes, we grumble about it, and then we get back to doing something more pleasant.
Where will you be on Groundhog’s Day 2016? What about 2020 or 2025? Unless you are Bill Murray or Andie MacDowell, answering this question and predicting the future can be tricky stuff. Yet Dell recently called together some friends to attempt just this sort of long-range prognostication around big data. I was recently joined on a discussion panel by the brilliant Rebekah Iliff (Chief Strategist at AirPR), the ever-curious Jai Menon (Chief Research Officer at Dell), and the lovely Matt Wolken (VP and GM of Dell Software), and then again with a wider group of technologists for a bigger roundtable.