Skip to main content

Hadoop is hot, Cloudera is 'sexy'


So, you heard it… Cloudera was the runner-up in ‘Sexiest Enterprise Startup’ category of The Crunchies. The awards were co-hosted by GigaOmVentureBeat and TechCrunch and aimed to recognize the most compelling startups, internet and technology innovations of the year. The ‘Sexiest Enterprise Startup’ award category was added this year where Box bagged the winning honor while Cloudera was honored with runner-up.


This is not the first award that Cloudera got and has made a habit of being at the right place at right time. Let’s analyze 5 key strategic moves that Cloudera has been making to keep it continually attractive:

1) Partners:

- Cloudera has association with some of the best names in the enterprise IT vendor world. During its initial euphoria Apache Hadoop started off a threat wave to relational database but today Cloudera seems to have settled to a symbiotic co-existence with IBM and Oracle products. Similarly, other hardware and software giants including Dell, HP, CISCO and NetApp add to this prestigious list of associations.  From a wider ecosystem perspective, Cloudera has 119 partners on last count.

2) Brand Ambassadors:

- If you are looking for Hadoop evangelists and brand ambassadors, look no further. Starting with Doug Cutting to the whole list of stars that address key note events and dominate media, Cloudera today has created many more brand ambassadors than any other startup in a similar time frame. Olson, Amr, Hammerbacher, Lipcon, White ... this Hadoop ambassador list is ever expanding and always seems to be adding Cloudera stars.

3) Go East, Go West:

- USA, UK and then Japan. Hey wait; are we talking Cars or IT? In a strategic move, Cloudera is one of the few companies who have established a key presence in Japanese market. Japan is one of the heavy industrialized nations which utilize IT for automation with intensive batch jobs. Some of the big names like Toshiba, Fujitsu have done PoC on Hadoop and Cloudera seems to have noticed that potential early enough.

4) Social Media and Search Engine optimization:

- Highly optimized website for search engine combined with smart social media campaigns from the company and individual contributor accounts, Cloudera has played smartly on digital presence. Unlike MapR which has relied quite a bit on PPC, Cloudera today has built up its online backlink and referral network aggressively in the last 2 years.

5) Influencer:

- There is bright talent pool at Cloudera not just in engineering staff but also within the Board and Management. While the engineers continue to make forays out of Cloudera starting up their own new ventures, the executives register their presence in some key venture funding decisions. Overall, a big big influencer in entire startup sphere.

The above points focus on aspects beyond its technical leadership and innovations. Last year, they demonstrated technical brilliance with real time querying in Impala and this year we can expect the momentum to add up with Trevni. Meanwhile, keep following and stay tuned.

___________________________________
image courtesy: freedigitalphotos.net

Comments

Popular posts from this blog

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 on how MapReduce and…

Pricing models for Hadoop products

A look at the various pricing models adopted by the vendors in the Hadoop ecosystem. While the pricing models are evolving in this rapid and dynamic market, listed below are some of the major variations utilized by companies in the sphere.
1) Per Node:Among the most common model, the node based pricing mechanism utilizes customized rules for determining pricing per node. This may be as straight forward as pricing per name node and data node or could have complex variants of pricing based on number of core processors utilized by the nodes in the cluster or per user license in case of applications.
2) Per TB:The data based pricing mechanism charges customer for license cost per TB of data. This model usually accounts non replicated data for computation of cost.
3) Subscription Support cost only:In this model, the vendor prefers to give away software for free but charges the customer for subscription support on a specified number of nodes. The support timings and level of support further …

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 Researchandthe IBM Cognos software group. This tool provides option to upload data sets and create visualizations including Scatter Plot, Tree Map, Tag/Word cloud and ge…