Welcome!

Microservices Expo Authors: Elizabeth White, Roger Strukhoff, Pat Romanski, Dana Gardner, Ruxit Blog

Related Topics: Microservices Expo, Microsoft Cloud, Open Source Cloud

Microservices Expo: Article

Making Sense of Large and Growing Data Volumes

MapReduce won’t overtake the enterprise data warehouse industry anytime soon

Is MapReduce the Holy Grail answer to the pressing problem of processing, analyzing and making sense of large and growing data volumes? Certainly it has potential in this arena, but there is a distressing gap between the amount of hype this technology - and its spinoffs - has received and the number of professionals who actually know how to integrate and make best use of it.

Industry watchers say it's just a matter of time before MapReduce sweeps through the enterprise data warehouse (EDW) market the same way open source technologies like Linux have done. In fact, in a recent blog post, Forrester's James Kobielus proclaimed that most EDW vendors will incorporate support for MapReduce's open source cousin Hadoop into the heart of their architectures to enable open, standards-based data analytics on massive amounts of data.

So, no more databases, just MapReduce? I'm not so sure. But don't misunderstand. It's not that MapReduce isn't an effective way to analyze data in some cases. The big names in Internet business are all using it - Facebook, Google, Amazon, eBay et al - so it must be good, right? But it's worth taking a more measured view based both on the technical and the practical business merits. I believe that the two technologies are not so mutually exclusive; that they will work hand-in-hand and, in some cases, MapReduce will be integrated into the relational database (RDBMS).

Google certainly has proven that MapReduce excels at making sense out of the exabytes of unstructured data on the web, which it should, given that MapReduce was designed from the outset for manipulating very large data sets. MapReduce in this sense provides a way to put structure around unstructured data. We humans prefer structure; it's in our DNA. Without structure, we have no real way of adding value to the data. Unstructured data analytics is something of an oxymoron for a pattern-seeking hominid.

MapReduce helps us put structure around the unstructured so we can then make sense of it. It creates an environment wherein a data analyst can write two simple functions, a "mapper" and a "reducer," to perform the actual data manipulation, returning a result that is at once both an analysis of the data it has just mapped and summarized, as well as the structure for further analysis that will help provide insight into the data. Whether that further analysis is done in a MapReduce environment might be the more appropriate question.

From an infrastructure standpoint, MapReduce excels where performance and scalability are challenges. Applications written using the MapReduce framework are automatically parallelized, making it well suited to a large infrastructure of connected machines. As it scales applications across lots of servers made up of lots of nodes, the MapReduce framework also provides built-in query fault tolerance so that whatever hardware component might fail, a query would be completed by another machine. Further, MapReduce and its open source brethren can perform functions not possible in standard SQL (click-stream sessionization, nPath, graph production of potentially unbounded length in SQL).

What's not to love? At a basic level I believe the MapReduce framework is an inefficient way of analyzing data for the vast majority of businesses. The aforementioned capabilities of MapReduce are all well and good, provided you have a Google-like business replete with legions of programmers and vast amounts of server and memory capacity. Viewed from this perspective, it makes perfect sense that Google developed and used MapReduce: because it could. It had a huge and growing resource in its farms of custom-made servers, as well as armies of programmers constantly looking for new ways to take advantage of that seemingly infinite hardware (and the data collected on it), to do cool new things.

Similarly, the other high-profile adopters and advocates are also IT-savvy, IT-heavy companies and, like Google, have the means and ongoing incentive to get a MapReduce framework tailored to their particular needs and reap the benefits. Would a mid-size firm know how? It seems doubtful. While it has claimed that MapReduce is easy to use, even for programmers without experience with distributed systems, I know from field experience with customers that it does, in fact, take some pretty experienced folks to make best use of it.

Projects like Hive, Google Sawzall, Yahoo Pig and companies like Cloudera all, in essence, attempt to make the MapReduce paradigm easier for lesser experts to use and, in fact, make it behave for the end user more like a parallel database. But this raises the question: Why? It seems to be a bit of re-inventing the wheel. IT-heavy is not how most businesses operate today, especially in these economic times. The dot-com bubble is long over. Hardware budgets are limited and few companies relish the idea of hiring teams of programming experts to maintain even a valuable IT asset such as their data warehouse. They'd rather buy an off-the-shelf tool designed from the ground up to do high-speed data analytics.

Like MapReduce, commercially available massively parallel processing databases specifically built for rapid, high volume data analytics will provide immense data scale and query fault tolerance. They also have a proven track record of customer deployments and deliver equal if not better performance on Big Data problems. Perhaps as important, today's next-generation MPP analytic databases give businesses the flexibility to draw on a deep pool of IT labor skilled in established conventions such as SQL.

As mentioned earlier, unstructured data seems like a natural for MapReduce analysis. A rising tide of chatter is focused on the increasing problem - and importance - of unstructured data. There is more than a bit of truth to this. As the Internet of everything becomes more and more a reality, data is generated everywhere; but our experience to date is that businesses are most interested in data derived from the transactional systems they've wired their businesses on top of, where structure is a given.

Another difficulty faces companies even as MapReduce becomes more integrated into the overall enterprise data analysis strategy. MapReduce is a framework. As the hype and interest have grown, MapReduce solutions are being created by database vendors in entirely non-standard and incompatible ways. This will further limit the likelihood that it will become the centerpiece of an EDW. Business has demonstrated time and again that it prefers open standards and interoperability.

Finally, I believe a move toward a programmer-centric approach to data analysis is both inefficient and contrary to all other prevailing trends of technology use in the enterprise. From the mobile workforce to the rise of social enterprise computing, the momentum is away from hierarchy. I believe this trend is the only way the problem of making Big Data actionable will be effectively addressed. In his classic book on the virtues of open source programming, The Cathedral and the Bazaar, Eric S. Raymond put forth the idea that open source was an effective way to address the complexity and density of information inherent in developing good software code. His proposition, "given enough eyeballs, all bugs are shallow," could easily be restated for Big Data as, "given enough analysts, all trends are apparent." The trick is - and really always has been - to get more people looking at the data. You don't achieve that end by centering your data analytics efforts on a tool largely geared to the skills of technical wizards.

MapReduce-type solutions as they currently exist are most effective when utilized by programmer-led organizations focused on maximizing their growing IT assets. For most businesses seeking the most efficient way to quickly turn their most valuable data into revenue generating insight, MPP databases will likely continue to hold sway, even as MapReduce-based solutions find a supporting role.

More Stories By Roger Gaskell

Roger Gaskell, CTO of Kognitio, has overall responsibility for all product development. He has been instrumental in all generations of the WX and WX2 database products to date, including evolving it from a database application running on proprietary hardware, to a software-only analytical database built on industry-standard blade servers.

Prior to Kognitio, Roger was test and development manager at AB Electronics for five years. During this time his primary responsibility was for the famous BBC Micro Computer and the development and testing of the first mass production of personal computers for IBM.

Comments (0)

Share your thoughts on this story.

Add your comment
You must be signed in to add a comment. Sign-in | Register

In accordance with our Comment Policy, we encourage comments that are on topic, relevant and to-the-point. We will remove comments that include profanity, personal attacks, racial slurs, threats of violence, or other inappropriate material that violates our Terms and Conditions, and will block users who make repeated violations. We ask all readers to expect diversity of opinion and to treat one another with dignity and respect.


@MicroservicesExpo Stories
Using new techniques of information modeling, indexing, and processing, new cloud-based systems can support cloud-based workloads previously not possible for high-throughput insurance, banking, and case-based applications. In his session at 18th Cloud Expo, John Newton, CTO, Founder and Chairman of Alfresco, described how to scale cloud-based content management repositories to store, manage, and retrieve billions of documents and related information with fast and linear scalability. He addres...
Cloud Expo 2016 New York at the Javits Center New York was characterized by increased attendance and a new focus on operations. These were both encouraging signs for all involved in Cloud Computing and all that it touches. As Conference Chair, I work with the Cloud Expo team to structure three keynotes, numerous general sessions, and more than 150 breakout sessions along 10 tracks. Our job is to balance the state of enterprise IT today with the trends that will be commonplace tomorrow. Mobile...
Akana has announced the availability of version 8 of its API Management solution. The Akana Platform provides an end-to-end API Management solution for designing, implementing, securing, managing, monitoring, and publishing APIs. It is available as a SaaS platform, on-premises, and as a hybrid deployment. Version 8 introduces a lot of new functionality, all aimed at offering customers the richest API Management capabilities in a way that is easier than ever for API and app developers to use.
SYS-CON Events announced today that Isomorphic Software will exhibit at DevOps Summit at 19th International Cloud Expo, which will take place on November 1–3, 2016, at the Santa Clara Convention Center in Santa Clara, CA. Isomorphic Software provides the SmartClient HTML5/AJAX platform, the most advanced technology for building rich, cutting-edge enterprise web applications for desktop and mobile. SmartClient combines the productivity and performance of traditional desktop software with the simp...
DevOps at Cloud Expo, taking place Nov 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA, is co-located with 19th Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world. The widespread success of cloud computing is driving the DevOps revolution in enterprise IT. Now as never before, development teams must communicate and collaborate in a dynamic, 24/7/365 environment. There is no time to wait for long dev...
SYS-CON Events announced today that 910Telecom will exhibit at the 19th International Cloud Expo, which will take place on November 1–3, 2016, at the Santa Clara Convention Center in Santa Clara, CA. Housed in the classic Denver Gas & Electric Building, 910 15th St., 910Telecom is a carrier-neutral telecom hotel located in the heart of Denver. Adjacent to CenturyLink, AT&T, and Denver Main, 910Telecom offers connectivity to all major carriers, Internet service providers, Internet backbones and ...
The burgeoning trends around DevOps are translating into new types of IT infrastructure that both developers and operators can take advantage of. The next BriefingsDirect Voice of the Customer thought leadership discussion focuses on the burgeoning trends around DevOps and how that’s translating into new types of IT infrastructure that both developers and operators can take advantage of.
With so much going on in this space you could be forgiven for thinking you were always working with yesterday’s technologies. So much change, so quickly. What do you do if you have to build a solution from the ground up that is expected to live in the field for at least 5-10 years? This is the challenge we faced when we looked to refresh our existing 10-year-old custom hardware stack to measure the fullness of trash cans and compactors.
This digest provides an overview of good resources that are well worth reading. We’ll be updating this page as new content becomes available, so I suggest you bookmark it. Also, expect more digests to come on different topics that make all of our IT-hearts go boom!
The emerging Internet of Everything creates tremendous new opportunities for customer engagement and business model innovation. However, enterprises must overcome a number of critical challenges to bring these new solutions to market. In his session at @ThingsExpo, Michael Martin, CTO/CIO at nfrastructure, outlined these key challenges and recommended approaches for overcoming them to achieve speed and agility in the design, development and implementation of Internet of Everything solutions wi...
19th Cloud Expo, taking place November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA, will feature technical sessions from a rock star conference faculty and the leading industry players in the world. Cloud computing is now being embraced by a majority of enterprises of all sizes. Yesterday's debate about public vs. private has transformed into the reality of hybrid cloud: a recent survey shows that 74% of enterprises have a hybrid cloud strategy. Meanwhile, 94% of enterpri...
Sharding has become a popular means of achieving scalability in application architectures in which read/write data separation is not only possible, but desirable to achieve new heights of concurrency. The premise is that by splitting up read and write duties, it is possible to get better overall performance at the cost of a slight delay in consistency. That is, it takes a bit of time to replicate changes initiated by a "write" to the read-only master database. It's eventually consistent, and it'...
To leverage Continuous Delivery, enterprises must consider impacts that span functional silos, as well as applications that touch older, slower moving components. Managing the many dependencies can cause slowdowns. See how to achieve continuous delivery in the enterprise.
Node.js and io.js are increasingly being used to run JavaScript on the server side for many types of applications, such as websites, real-time messaging and controllers for small devices with limited resources. For DevOps it is crucial to monitor the whole application stack and Node.js is rapidly becoming an important part of the stack in many organizations. Sematext has historically had a strong support for monitoring big data applications such as Elastic (aka Elasticsearch), Cassandra, Solr, S...
Thomas Bitman of Gartner wrote a blog post last year about why OpenStack projects fail. In that article, he outlined three particular metrics which together cause 60% of OpenStack projects to fall short of expectations: Wrong people (31% of failures): a successful cloud needs commitment both from the operations team as well as from "anchor" tenants. Wrong processes (19% of failures): a successful cloud automates across silos in the software development lifecycle, not just within silos.
There's a lot of things we do to improve the performance of web and mobile applications. We use caching. We use compression. We offload security (SSL and TLS) to a proxy with greater compute capacity. We apply image optimization and minification to content. We do all that because performance is king. Failure to perform can be, for many businesses, equivalent to an outage with increased abandonment rates and angry customers taking to the Internet to express their extreme displeasure.
Right off the bat, Newman advises that we should "think of microservices as a specific approach for SOA in the same way that XP or Scrum are specific approaches for Agile Software development". These analogies are very interesting because my expectation was that microservices is a pattern. So I might infer that microservices is a set of process techniques as opposed to an architectural approach. Yet in the book, Newman clearly includes some elements of concept model and architecture as well as p...
A company’s collection of online systems is like a delicate ecosystem – all components must integrate with and complement each other, and one single malfunction in any of them can bring the entire system to a screeching halt. That’s why, when monitoring and analyzing the health of your online systems, you need a broad arsenal of different tools for your different needs. In addition to a wide-angle lens that provides a snapshot of the overall health of your system, you must also have precise, ...
SYS-CON Events announced today that Venafi, the Immune System for the Internet™ and the leading provider of Next Generation Trust Protection, will exhibit at @DevOpsSummit at 19th International Cloud Expo, which will take place on November 1–3, 2016, at the Santa Clara Convention Center in Santa Clara, CA. Venafi is the Immune System for the Internet™ that protects the foundation of all cybersecurity – cryptographic keys and digital certificates – so they can’t be misused by bad guys in attacks...
Monitoring of Docker environments is challenging. Why? Because each container typically runs a single process, has its own environment, utilizes virtual networks, or has various methods of managing storage. Traditional monitoring solutions take metrics from each server and applications they run. These servers and applications running on them are typically very static, with very long uptimes. Docker deployments are different: a set of containers may run many applications, all sharing the resource...