Data Splice

The top two of the Superman-Hadoop start-up This is no longer a secret, global data is growing geometrically, with the wave of data growing rapidly around the world in a large number of hadoop start-ups. As an open source branch of Apache, Hadoop has almost become a surrogate for large data. Gartner estimates that the current market value of the Hadoop ecosystem is about 77,000,000, which the research company expects will increase rapidly to 813 million by 2016 ...

This week, splice machine, a big data start-up, completed a 4 million dollar a round of funding to build a SQL database on the Open-source Hadoop Distributed File System, MONGOHQ $6 million in investment to develop its developer-oriented database services BloomReach received 25 million dollars in investment to further expand the application of large data marketing. The recent developments in these three companies have amply demonstrated why investors are pouring money into big data start-ups because of the increasing use of large data ...

In the week, 3 Big data startups got high investments: Splice Machine received $4 million in funding to develop a SQL engine for large data applications; MONGOHQ $6 million in investment to improve its database services BloomReach 25 million dollars in investment and will be used for large data application development. What is the reason for VC to big data favor? The three companies themselves are the answer. Splice machine executives say that using Splice's SQL engine ...

At the moment, "big data" has become one of the hottest technical terms of the 2013, and in the past year, the growth and change of the market is not insignificant. At the same time, we have seen a change in the use of Hadoop and its ecosystem from top technical talent to data scientists. More and more enterprises embrace large data technology and apply it to production environment. So what will happen to the trend of big data in the 2014, and here's a look at 12 predictions from CIOs: 1. People stop talking about big data for 2014, and big data stops saying ...

Open source Large data frame Apache Hadoop has become a fact standard for large data processing, but it is also almost synonymous with large numbers, although this is somewhat biased. 　　According to Gartner, the current market for Hadoop ecosystems is around $77 million trillion, which will grow rapidly to $813 million in 2016. But it's not easy to swim in the fast-growing blue sea of Hadoop, it's hard to develop large data infrastructure technology products, and it's hard to sell, specifically ...

Open source Large data frame Apache Hadoop has become a fact standard for large data processing, but it is also almost synonymous with large numbers, although this is somewhat biased. According to Gartner, the current market for Hadoop ecosystems is around $77 million trillion, which will grow rapidly to $813 million in 2016. But it's not easy to swim in the fast-growing blue sea of Hadoop, not only is it hard to develop large data infrastructure technology products, but it's hard to sell, particularly to big data infrastructures ...

Open source Large data frame Apache Hadoop has become a fact standard for large data processing, but it is also almost synonymous with large numbers, although this is somewhat biased. According to Gartner, the current market for Hadoop ecosystems is around $77 million trillion, which will grow rapidly to $813 million in 2016. But it's not easy to swim in the fast-growing blue sea of Hadoop, not only is it hard to develop large data infrastructure technology products, but it's hard to sell, particularly to big data infrastructures ...

When Hadoop enters the enterprise, it must face the problem of how to address and respond to the traditional and mature it information architecture. 　　In the industry, how to deal with the original structured data is a difficult problem for enterprises to enter large data field. When Hadoop enters the enterprise, it must face the problem of how to address and respond to the traditional and mature it information architecture. In the past, MapReduce was mainly used to solve unstructured data such as log file analysis, Internet click Stream, Internet index, machine learning, financial analysis, scientific simulation, image storage and matrix calculation. But ...

Now, "Big data" has become one of the hottest words, more and more enterprises began to pay attention to and embrace large data, 2014 Big data will have more substantial progress, in which Hadoop and R language will be the protagonist. "Big Data" has become one of the most frequently used technical hot words in the 2013. The corresponding market has also seen rapid growth in the year. Hadoop and its ecosystems, which are associated with large data, have become a common tool for data scientists from technologies that were previously used by very talented programmers and engineers. More and more enterprises begin to embrace ...

Now, "Big data" has become one of the hottest words, more and more enterprises began to pay attention to and embrace large data, 2014 Big data will have more substantial progress, in which Hadoop and R language will be the protagonist. "Big Data" has become one of the most frequently used technical hot words in the 2013. The corresponding market has also seen rapid growth in the year. Hadoop and its ecosystems, which are associated with large data, have become a common tool for data scientists from technologies that were previously used by very talented programmers and engineers. More and more enterprises begin to embrace ...