"2013 retrospect" big Data flash Year

In 2013, "Big Data" replaced "cloud computing" as the most sought-after it hot word. However, this technology concept is still a long way from vigorous application.

Over the past year, large data has been mentioned frequently on a wide variety of occasions, and the technical conference on large data subjects is your song. According to the technology maturity curve of the research institute Gartner, the big data at this stage are climbing to the peak of the so-called "expected expansion period". While in the evolution of large data technologies, we saw a lot of progress in 2013, including a new upgrade of the open source framework for Hadoop and the rise of emerging companies, but at the practical level, large data applications are still in the early stages of practice.

According to Gartner's forecasts, big data will generate 34 billion of billions of dollars in IT spending in 2013, which is expected to grow 3 times times by 2018. The October 2013 generic version of Hadoop 2.0 released by the Apache Foundation is undoubtedly a big event in the Big data field. The performance of Hadoop 2.0 has increased significantly compared to the previous version. For mapreduce tasks, Hadoop is just a batch data processing framework. Now Hadoop 2.0 is a common framework for deploying applications across node systems, and MapReduce can also run across nodes. The newly released yarn (verb Another Resource negotiator, another resource coordinator) is more open, and this new execution layer eliminates the strict subordination of the Hadoop environment on MapReduce.

On the entrepreneurial side, after Splunk's successful IPO in 2012 (initial public offerings), and quickly gained nearly 1.6 billion dollars in market capitalisation, MongoDB became a start-up upstart in the Big data field of 2013. The company, founded in 2007, has recently gained 231 million of billions of dollars in funding, making it the first open source venture to be worth more than 1 billion dollars. At present, the industry's valuation of the company's assets is as high as $1.2 billion trillion, MongoDB is expected to conduct an IPO. The rapid rise of MongoDB has proved that large data areas have sufficient capital. In addition to MongoDB, Hortonworks received 50 million of dollars in financing, DataStax received 45 million U.S. dollars in financing, Couchbase received 25 million dollars in financing.

On the other hand, the industry as a whole (including technology providers, solution providers, enterprise customers) is further clarifying the positioning of large data in the enterprise IT overall architecture. In 2013, we heard less about "whether big data will replace BI?" "To make a heated argument. The focus of the industry focuses instead on the combination of big data technology and traditional database technology. Although the rise of large data technology and Internet enterprises to control the demand of large-scale newborn data is inseparable, but in the "mainstream" process, the integration of distributed technology and traditional SQL database, traditional analysis and display technology in the role of large data platform, is being recognized by more and more enterprises.

As the industry's understanding of large data technology is deepening, large data ecosystems are being perfected, and the process of coexistence and integration between Hadoop, NoSQL and SQL is unfolding, and the maturity of technology is increasing. It is relatively regrettable that, at the application level, the actual deployment has not yet been carried out on a large scale. Although many conservative enterprise customers have begun to change their attitudes, most of the early practices are still dominated by marginal attempts, and the core position and industry attributes of large data technology applications in the enterprise have not yet really formed. This also means that big data still has too much room for effort in the real world.

Big data trends that deserve attention in the 2014

Ovum, a neutral consultancy, expects that in 2014, an increasing number of third-party vendors and IT service ecosystems will begin to launch tools and solutions for large data in enterprise data warehouses and application markets. This trend is a diversification of the SQL and Hadoop platforms and provides an inevitable result of overlapping functions. Ovum that the big data trends that deserve attention in 2014 include:

The analysis data platform is adding more functionality;

Large-Data Enterprise application market is emerging;

the development of NoSQL;

Data layering begins to dominate the real-time data platform.

In addition, the emerging technologies, represented by Hadoop, will continue to integrate data from multiple sources and constantly expand their predictive analytics capabilities to bring more extensive application experience to enterprise customers. In fact, Hadoop continues to evolve toward the goal of "enterprise data management key components," which will be an important part of the enterprise computing infrastructure, and data analysis will be the first choice for companies to develop large data practices. In terms of security and operation Management, Hadoop is expected to be more functional and more standardized and standardized, and thus win more trust from enterprise customers.