Skip to main content

Top Big Data influencers of 2013

Top Big Data influencer Badge
As we end the year 2013, lets take stock of top influencers in Big Data for 2013. The list is an annual snapshot of people, organizations, products and themes that exercised most influence on the Big Data and Hadoop ecosystem in the year. Click here to read the methodology used


Matt Aslett As research Director for data management and analytics, Matt became one of the most known names in ecosystem with Database landscape map. Resembling a city's metro train network, the chart became a de-facto reference containing names of players in all major variants of database. (Although, the chart was not published this year, it went viral towards the beginning of new year and end of last year.)
Tony Baer Tony Baer leads Ovum’s Big Data research area. With his insightful thoughts via Ovum engagements and other social media channels like blog, Tony continues to unravel deep layers within the ecosystem and complexities around product evolution.
Merv Adrian Merv Adrian, Research VP at Gartner, was one of the most visible faces this year from Gartner and analysts' space featuring at summits, interviews, client engagements and social media. Although Gartner struck a discordant note earlier in the year with "Trough of Disillusionment" remark on Big Data, Svetlana Sicular and Mark Beyer cleared the air further with cautious optimism notes.

Online Media:

News and Opinion:

Derrick Harris GigaOm's Derrick Harris covered some of the most topical themes around Big Data and Hadoop through the year. Not just focusing on developing news stories, Derrick gave bigger insights into technology and it's use cases at various organizations.

Blogs and Curated content:

Alexandru Popescu Alex with his curated blog called myNoSQL and community driven InfoQ continued to drive conversation around some of the most notable stories of the year. Rarely mincing words, he continues to draw big traffic to his blogs.

Focused content:

IBM IBM drove across the message around Big Data initiatives in online media through multiple channels. The notables one include IBM Data Magazine (weekly publication of articles), IBM Big Data Hub (topical blogs, videos), IBM Developer Works (technical guidance articles) and IBM Journals. Combined together, the reach and traffic surpasses many other media competitors and other promoted content from software vendors.


Hadapt Hadapt did not come up with it's tech break-through this year but it had actually set the pigeon among the cats much earlier. With its SQL + PostgreSQL on Hadoop nodes offering, it set a commercial precedent for others to follow. And, what a race did this set off! Following last year's Cloudera Impala, almost everyone from Hortonworks, EMC, IBM and a host of other vendors brought out products in the SQL on Hadoop layer.
Vivisimo Vivisimo was earlier acquired by IBM and is now called InfoSphere Data Explorer. With its federated search function, it offers search over various data sources including HDFS. It was among the first major commercial product to exhibit leadership in search function on top of Hadoop. As a major trend which came up this year, Hadoop market leader Cloudera and MapR did not disappoint with technical innovation in this area and we expect more to follow.
SAP HANA  SAP, the big gorilla in enterprise software set the ball rolling for wider adoption of In Memory Computing (IMC) with SAP HANA. With HANA becoming an integral part of SAP deployments and upgrade plans, the rest of enterprise market was quick to follow suit. Oracle, IBM and the rest have now IMC as part of their standard database products rather than fancy acquisitions on the shelf.


ASF Apache Software Foundation continued to incubate newer projects and graduate others within the Hadoop ecosystem. With Hadoop being one of the biggest success in recent history of open source software, ASF continued to take pride in driving the community.
GitHub The octocat remained the preferred repository of people across the organizations and individual developers. While Twitter released its 100th open source repo on GitHub, others like Cloudera, Facebook and the likes also hosted their components and projects.
Google Code For the utilities, scripts and other hacks, Google code remained a preferred repository among the developers. Integrated with Google account single sign on and git tools, it offered ease of use to developers.

Social Media:

D J Patil Former LinkedIn senior executive and currently entrepreneur in residence at Greylock Partners, D J Patil (@dpatil) is also co-credited for the coining the term 'data scientist'. He established an enviable Twitter presence with relevant messages and conversations.
Gregory Piatetsky-Shapiro Gregory Piatetsky-Shapiro, Ph.D. (@kdnuggets) is the President of Kdnuggets consulting and founder of KDD (Knowledge Discovery and Data mining conferences). His site and tweets continued to attract substantial traffic and referrals to the outbound links.
Tweet Chat Entrepreneurs like John Furrier(@furrier) of Silicon Angle with novel Crowd Chat and evangelists like James Kobielus (@jameskobielus‎) with tweet chats found new methods of engaging online community. Coupled with events, these chats drove conversation and engaged thought leaders.

Stock Performers:

Splunk Splunk (NASDAQ: SPLK) continued to trade at life time high levels and scorch the market (despite losses). Splunk sets a great stock precedent for machine log analytics and big data companies.
Tableau Listed with the dream symbol DATA, the visualization software company Tableau has made good progress on stock market since its IPO this year. Tableau's $254.2 million IPO vis-a-vis $45 million VC funding ensured we have another reason to continue investing in similar companies.
Rocket Fuel Rocket Fuel (NASDAQ:FUEL), a digital advertising company listed on stock exchange this year and its stock went from $29 to $56.10 in its debut, raising $116 million for the company and reaching a valuation of about $1.8 billion. Among the sponsors of this year's Hadoop Summit, Rocket Fuel has been one of the early adopters of Hadoop. We expect more from ad tech industry to follow Rocket Fuel's public listing path.
Top Big Data ecosystem influencers of 2013

Top Big Data influencers of 2014 >>

<< Archive Link : Big Data Influencers of 2012


  1. A lot is buzzing around Big Data. Listing the best ones of the year is indeed a tough Job. Well done! The methodology is impressive and up to the mark. Hadoop remains the first choice by companies like Amazon, Intel, Pivot Solutions, QBurst and MapR Technologies. The expandability of open source software is well utilized by these companies using Hadoop.


Post a Comment

Popular articles

5 online tools in data visualization playground

While building up an analytics dashboard, one of the major decision points is regarding the type of charts and graphs that would provide better insight into the data. To avoid a lot of re-work later, it makes sense to try the various chart options during the requirement and design phase. It is probably a well known myth that existing tool options in any product can serve all the user requirements with just minor configuration changes. We all know and realize that code needs to be written to serve each customer’s individual needs. To that effect, here are 5 tools that could empower your technical and business teams to decide on visualization options during the requirement phase. Listed below are online tools for you to add data and use as playground. 1)      Many Eyes : Many Eyes is a data visualization experiment by IBM Research and the IBM Cognos software group. This tool provides option to upload data sets and create visualizations including Scatter Plot, Tree Ma

Data deduplication tactics with HDFS and MapReduce

As the amount of data continues to grow exponentially, there has been increased focus on stored data reduction methods. Data compression, single instance store and data deduplication are among the common techniques employed for stored data reduction. Deduplication often refers to elimination of redundant subfiles (also known as chunks, blocks, or extents). Unlike compression, data is not changed and eliminates storage capacity for identical data. Data deduplication offers significant advantage in terms of reduction in storage, network bandwidth and promises increased scalability. From a simplistic use case perspective, we can see application in removing duplicates in Call Detail Record (CDR) for a Telecom carrier. Similarly, we may apply the technique to optimize on network traffic carrying the same data packets. Some of the common methods for data deduplication in storage architecture include hashing, binary comparison and delta differencing. In this post, we focus o

In-memory data model with Apache Gora

Open source in-memory data model and persistence for big data framework Apache Gora™ version 0.3, was released in May 2013. The 0.3 release offers significant improvements and changes to a number of modules including a number of bug fixes. However, what may be of significant interest to the DynamoDB community will be the addition of a gora-dynamodb datastore for mapping and persisting objects to Amazon's DynamoDB . Additionally the release includes various improvements to the gora-core and gora-cassandra modules as well as a new Web Services API implementation which enables users to extend Gora to any cloud storage platform of their choice. This 2-part post provides commentary on all of the above and a whole lot more, expanding to cover where Gora fits in within the NoSQL and Big Data space, the development challenges and features which have been baked into Gora 0.3 and finally what we have on the road map for the 0.4 development drive. Introducing Apache Gora Although