One of the key decisions faced by enterprises that perform large data projects is which database to use, SQL or NoSQL? SQL has impressive performance, a huge installation base, and NoSQL is gaining considerable revenue and has many supporters. Let's take a look at the views of two experts on this issue. Experts· VOLTDB's chief technology officer, Ryan Betts, says that SQL has won widespread deployments of large companies, and that big data is another area that it can support. Couchba ...
One of the key decisions that companies that perform large data [note] projects face is which database to use, SQL or NoSQL? SQL has impressive performance, a huge installation base, and NoSQL is gaining considerable revenue and has many supporters. Let's take a look at the views of two experts on this issue. Experts· VOLTDB's chief technology officer, Ryan Betts, says that SQL has won widespread deployments of large companies, and that big data is another area that it can support. Couch ...
The greatest fascination with large data is the new business value that comes from technical analysis and excavation. SQL on Hadoop is a critical direction. CSDN Cloud specifically invited Liang to write this article, to the 7 of the latest technology to do in-depth elaboration. The article is longer, but I believe there must be a harvest. December 5, 2013-6th, "application-driven architecture and technology" as the theme of the seventh session of China Large Data technology conference (DA data Marvell Conference 2013,BDTC 2013) before the meeting, ...
In the context of large data, Microsoft does not seem to advertise their large data products or solutions in a high-profile way, as other database vendors do. And in dealing with big data challenges, some internet giants are on the front, like Google and Yahoo, which handle the amount of data per day, a large chunk of which is a document based index file. Of course, it is inaccurate to define large data so that it is not limited to indexes, e-mail messages, documents, Web server logs, social networking information, and all other unstructured databases in the enterprise are part of the larger data ...
As a software developer or DBA, one of the essential tasks is to deal with databases, such as MS SQL Server, MySQL, Oracle, PostgreSQL, MongoDB, and so on. As we all know, MySQL is currently the most widely used and the best free open source database, in addition, there are some you do not know or useless but excellent open source database, such as PostgreSQL, MongoDB, HBase, Cassandra, Couchba ...
Would you like to run the database server on the IaaS cloud? Or should it be converted to a PAAs selection? The choice of a database as a service may sound tempting, such as Cloudant's nosql but how to weigh it? Developers and application designers have a lot of options for deploying databases in the cloud, and it's hard to make the best decisions. Regardless of which cloud database you choose, you need to measure a variety of factors, including cost, availability, scalability, and performance support. The current code may be difficult to select from the platform, the Service (PaaS) database, or even the relational database ...
Social media, E-commerce, mobile communications, and machine-machine data exchange make terabytes or even petabytes of data that the enterprise IT department must store and process. Mastering fragmentation best practices is a very important step in the cloud planning process when users process data for cloud computing databases. Fragmentation is the process of splitting a table into a manageable size disk file. Some highly resilient key-value data stores, such as Amazon simple DB, Google App engine ...
Microsoft customers running SQL Server will gain real big http://www.aliyun.com/zixun/aggregation/14345.html > Data processing capabilities through the introduction of Hadoop. Microsoft has released early-stage code that allows customers to access the Java architecture to SQL Server 2008 R2, SQL Server Parallel Data Warehouse, and the next generation of Microsoft ...
SQL Server introduces http://www.aliyun.com/zixun/aggregation/14255.html ">hadoop large data processing capacity release time: 2012.05.11 14:48 Source: Engine Room 360 Author: Computer room 360 Microsoft has released early code, so that customers can put this ja ...
Google created a mapreduce,mapreduce cluster in 2004 that could include thousands of parallel-operation computers. At the same time, MapReduce allows programmers to quickly transform data and execute data in such a large cluster. From MapReduce to Hadoop, this has undergone an interesting shift. MapReduce was originally a huge amount of data that helped search engine companies respond to the creation of indexes created by the World Wide Web. Google initially recruited some Silicon Valley elites and hired a large number of engineers to ...
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