Vertica Database Architecture

When it comes to big data, many people first think of internet companies, such as Google, Baidu and Alibaba. Internet companies in the large data analysis has indeed walked in the forefront of the industry, its aura also obscured the industry's big data shine. IDC defines big data with "4 V": volume represents greater capacity, produced represents a variety of data, velocity represents faster processing speed, and value means that large data can create more value. Tianjin Nanda General Data Technology Co., Ltd. (hereinafter referred to as the General) chief technical Officer Vounie said, such as ...

In the siege of large manufacturers such as Oracle, IBM and Microsoft, domestic database makers are still struggling to survive. This is an undeniable fact that the database market is close to saturation, especially in the face of the relationship between the transaction database field, foreign manufacturers start early, rich in resources, and also continue to encroach on the market segments, has formed a huge advantage. Faced with this situation, the South's general CTO Vounie that the domestic database manufacturers have missed the best time, should not take their own short board (OLTP) to go head-to-head, but should be in the direction of OLAP. Accompanied by large data ...

In the siege of large manufacturers such as Oracle, IBM and Microsoft, domestic database makers are still struggling to survive. This is an undeniable fact that the database market is close to saturation, especially in the face of the relationship between the transaction database field, foreign manufacturers start early, rich in resources, and also continue to encroach on the market segments, has formed a huge advantage. Faced with this situation, the South's general CTO Vounie that the domestic database manufacturers have missed the best time, should not take their own short board (OLTP) to go head-to-head, but should be in the direction of OLAP. Accompanied by large data ...

"IT168" I have always felt that nosql in fact very easy to understand, I have also had a very in-depth study of NoSQL, but in the recent preparation of yuntable chart, found that NoSQL not only very profound, 　　And my personal understanding of NoSQL is only superficial, but I am still a "shame and then Yong" people, so after a period of study, from the sixth part of this series, will talk to you nosql, and this article will be the main to do a NoSQL database review. ...

Michael Stonebraker is a pioneer in the field of databases. His deep expertise has also helped to develop some of the most popular database systems such as Postgres, Ingres and Vertica. One of his most recent studies is VoltDB, a memory-based OLTP (Online Transaction Processing) system, which he claims is two orders of magnitude faster than traditional solutions. However, Stonebraker's opinion has been controversial over the years, on the one hand being ...

June 20 HP released Vertica Analytics Platform version 5.0, the latest edition will be combined with HP's own hardware products. HP acquired Vertica earlier this year, which will help HP play a key role in the growing number of data markets. Vertica is based on column storage. The design based on column storage has great advantage over traditional row-oriented storage database. At the same time Vertica support MPP (massively parallel processin ...

As data grows in hundreds of terabytes, we need a unique technology to address this unprecedented challenge. Big data analysis ushered in the great era of the global organizations of all walks of life have realized that the most accurate business decisions from the facts, not a figment of the imagination. This means that they need to use the decision model and technical support based on data analysis in addition to the historical information of the internal trading system. Internet-clicked data, sensing data, log files, mobile data with rich geospatial information and various kinds of comments involving the network have become various forms of mass information. ...

The amount of data used for SaaS applications is facing a TB-level growth rate, with different SaaS applications, and not exactly the same data structure, with text, graphics, and even small databases. 　　With the distributed characteristics of the cloud service platform, the SaaS application data can be distributed on different servers, and how to data mining the heterogeneous data is a difficult problem faced by the enterprises in cloud era. The challenge of enterprise data mining in cloud era mining efficiency: After entering the cloud computing era, BI's thinking has been transformed. Previously based on closed enterprise data Mining ...

As data grows in hundreds of terabytes, we need a unique technology to address this unprecedented challenge. Big data analysis ushered in the great era of the global organizations of all walks of life have realized that the most accurate business decisions from the facts, not a figment of the imagination. This means that they need to use the decision model and technical support based on data analysis in addition to the historical information of the internal trading system. Internet-clicked data, sensing data, log files, mobile data with rich geospatial information and various kinds of comments involving the network have become various forms of mass information. Have a great ...

The concept of large data, for domestic enterprises may be slightly unfamiliar, the mainland is currently engaged in this area of small enterprises. But in foreign countries, big data is seen by technology companies as another big business opportunity after cloud computing, with a large number of well-known companies, including Microsoft, Google, Amazon and Microsoft, that have nuggets in the market. In addition, many start-ups are also starting to join the big-data gold rush, an area that has become a real Red sea. In this paper, the author of the world today in the large data field of the most powerful enterprises, some of them are computers or the Internet field of the Giants, there are ...