Nosql Wide Column Store

Within a few years, the NoSQL database has focused attention on performance, scalability, flexible patterns, and analytical capabilities. 　　Although relational databases are still a good choice for some use cases, like structural data and applications that require acid transactions, NoSQL is more advantageous in the following use cases: The data stored is essentially semi-structured or loosely-structured. 　　Requires a certain level of performance and scalability. 　　The application to access the data is consistent with the final consistency. Non-relational databases typically support the following features: Flexible ...

In the past few years, relational databases have been the only choice for data persistence, and data workers are considering only filtering in these traditional databases, such as SQL Server, Oracle, or MySQL. Even make some default choices, such as using. NET will typically choose SQL Server, and Java may be biased toward Oracle,ruby, Mysql,python is PostgreSQL or MySQL, and so on. The reason is simple: In the past a long time, the relational database is robust ...

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 ...

The appearance of MapReduce is to break through the limitations of the database. Tools such as Giraph, Hama and Impala are designed to break through the limits of MapReduce. 　　While the operation of the above scenarios is based on Hadoop, graphics, documents, columns, and other NoSQL databases are also an integral part of large data. 　　Which large data tool meets your needs? The problem is really not easy to answer in the context of the rapid growth in the number of solutions available today. Apache Hado ...

With the development of the Internet, mobile Internet and IoT, no one can deny that we have actually ushered in a massive data era, data research company IDC expects 2011 total data will reach 1.8 trillion GB, the analysis of these massive data has become a very important and urgent demand. As an Internet data analysis company, we are "revolt" in the field of analysis of massive data. Over the years, with stringent business requirements and data pressures, we've tried almost every possible big data analysis method, and finally landed on the Hadoop platform ...

Cassandra and HBase are the representatives of many open source projects based on bigtable technology that are implementing high scalability, flexibility, distributed, and wide-column data storage in different ways. In this new area of big data [note], the BigTable database technology is well worth our attention because it was invented by Google, and Google is a well-established company that specializes in managing massive amounts of data. If you know this very well, your family is familiar with the two of Cassandra and HBase.

From the 2008 60-man "Hadoop in China" technology salon, to the current thousands of-person scale of the industry technology feast, the seven-year BDTC (large data technology conference) has fully witnessed the transformation of China's large data technology and applications, faithfully depicting the large data field of technology hotspots, Precipitated countless valuable industry experience. At the same time, from December 2014 12 to 14th, the largest China data technology event will continue to lead the current field of technology hotspots, sharing the industry experience. In order to better understand the trend of industry development, understanding of enterprises ...

Star Ring Technology's core development team participated in the deployment of the country's earliest Hadoop cluster, team leader Sun Yuanhao in the world's leading software development field has many years of experience, during Intel's work has been promoted to the Data Center Software Division Asia Pacific CTO. In recent years, the team has studied large data and Hadoop enterprise-class products, and in telecommunications, finance, transportation, government and other areas of the landing applications have extensive experience, is China's large data core technology enterprise application pioneers and practitioners. Transwarp Data Hub (referred to as TDH) is the most cases of domestic landing ...

To understand the concept of large data, first from the "Big", "big" refers to the scale of data, large data generally refers to the size of the 10TB (1TB=1024GB) data volume above. Large data is different from the massive data in the past, and its basic characteristics can be summed up with 4 V (Vol-ume, produced, and #118alue和Veloc-ity), that is, large volume, diversity, low value density and fast speed. Large data features first, the volume of data is huge. Jump from TB level to PB level. Second, the data types are numerous, as mentioned above ...