Querying Relational Data

This article will introduce big SQL, which answers many common questions about this IBM technology that users of relational DBMS have. Large data: It is useful for IT professionals who analyze and manage information. But it's hard for some professionals to understand how to use large data, because Apache Hadoop, one of the most popular big data platforms, has brought a lot of new technology, including the newer query and scripting languages. Big SQL is IBM's Hadoop based platform Infosphere Biginsight ...

"51CTO exclusive feature" 2010 should be remembered, because the SQL will die in the year. This year's relational database is on the go, and this year developers find that they don't need long, laborious construction columns or tables to store data. 2010 will be the starting year for a document database. Although the momentum has been going on for years, now is the age when more and more extensive document databases appear. From cloud-based Amazon to Google, a number of open-source tools, along with the birth of Couchdb and MongoDB. So what ...

As two of the most popular technologies in the field of information management, the hardware architecture of database integration machine and large data technology is basically the same, but the software system has the essential difference, which leads to the different characteristic performance. With the rapid growth of enterprise data and the continuous improvement of users ' requirements for service level, the traditional relational database technology has shown obvious lack of ability in production practice for a long time. How to obtain high availability of massive data at reasonable cost has become a major challenge in modern it field. In order to meet this challenge, in recent years, it market ...

There are many methods for processing and analyzing large data in the new methods of data processing and analysis, but most of them have some common characteristics. 　　That is, they use the advantages of hardware, using extended, parallel processing technology, the use of non-relational data storage to deal with unstructured and semi-structured data, and the use of advanced analysis and data visualization technology for large data to convey insights to end users. 　　Wikibon has identified three large data methods that will change the business analysis and data management markets. Hadoop Hadoop is a massive distribution of processing, storing, and analyzing ...

The development of any new technology will undergo a process from the public to the final universal application. Large data technology as a new data processing technology, after nearly a decade of development, has just begun to be applied in various industries. But from the media and public view, the big data technology always has the mysterious color, appears to have the magical power which digs the wealth and forecasts the future. Widely circulated large data applications include the target supermarket based on the girl's shopping history to determine whether pregnancy, credit card companies based on the user in different time and space shopping behavior to predict the customer's next purchase behavior, and so on. Large Data Technology ...

It's really tempting to get business on big Data technology, and Apache Hadoop makes the temptation more violent. Hadoop is a large scale scalable data storage platform that forms the foundation of most large data projects. Hadoop is powerful, but it requires the company to invest a lot of learning energy and other resources. If you get the right application, Hadoop can actually improve your company's business, but the application of this hadoop is fraught with thorns. On the other side, many businesses (not Google, of course) ...

BEIJING, July 22, 2014--companies are looking for innovative ways to manage as many data and data sources as possible. While technologies such as Hadoop and NoSQL provide specific ways to deal with large data problems, these technologies may introduce islands of data that can complicate data access and data analysis needed to form critical insights. In order to maximize the value of information and better handle large data, enterprises need to gradually change the data management architecture into a large data management system to seamlessly integrate various sources, all types of data, including Hadoop, relational databases, and nos ...

It's really tempting to get business on big Data technology, and Apache Hadoop makes the temptation more violent. Hadoop is a large scale scalable data storage platform that forms the foundation of most large data projects. Hadoop is powerful, but it requires the company to invest a lot of learning energy and other resources. If you get the right application, Hadoop can actually improve your company's business, but the application of this hadoop is fraught with thorns. On the other side, many businesses (not Google, of course) ...

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 ...

Open source data is divided into two factions, NoSQL enthusiasts like to publish a lengthy criticism of relational database limitations, MySQL enthusiasts stubbornly defend the health relational database-insist that the data neatly stored in the table. 　　You'd think the two sides would never get along, but in fact, tens of thousands of companies have been trying to combine relational and relational databases, and have tried it many years ago. But the development of new technologies is often antithetical to the technology of the past. When NoSQL developed, the name of the light sounded like ...