Azure Nosql Mongodb

Kgroup develops and implements content management and distribution solutions for corporate and public Web sites and for network TV. Kgroup is headquartered in Milan, has been operating in Italy and Europe for more than 10 years, the latest product is the Qoob Content management architecture. Overview Kgroup has completed many large and small content management projects, so we are well aware of the need for continuous innovation in the Web world. Today's web content includes standard content types (text, pictures, audio, video, and so on), as well as custom content types dedicated to customer scenarios, such as internal and ...

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 ...

Today's article comes from 10gen software engineer Sridhar Nanjundeswaran. 10gen developed the http://www.aliyun.com/zixun/aggregation/13461.html ">mongodb, and provides product support, training and open source database consulting." We are excited about the continuous cooperation between 10gen and Microsoft. We are actively leveraging the new features of Windows Azure to ensure that wind ...

Forbes: hadoop--Big Data tools you have to understand now Apache Hadoop has become the driving force behind the development of the big data industry. Techniques such as hive and pig are often mentioned, but they all have functions and why they need strange names (such as Oozie,zookeeper, Flume). Hadoop has brought in cheap processing of large data (large data volumes are usually 10-100GB or more, with a variety of data types, including structured, unstructured, etc.) capabilities. But this is the same as before ...

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 ...

Top Ten Open Source technologies: Apache HBase: This large data management platform is built on Google's powerful bigtable management engine. As a database with open source, Java coding, and distributed multiple advantages, HBase was originally designed for the Hadoop platform, and this powerful data management tool is also used by Facebook to manage the vast data of the messaging platform. Apache Storm: A distributed real-time computing system for processing high-speed, large data streams. Storm for Apache Had ...

Big data has grown rapidly in all walks of life, and many organizations have been forced to look for new and creative ways to manage and control such a large amount of data, not only to manage and control data, but to analyze and tap the value to facilitate business development. Looking at big data, there have been a lot of disruptive technologies in the past few years, such as Hadoop, Mongdb, Spark, Impala, etc., and understanding these cutting-edge technologies will also help you better grasp the trend of large data development. It is true that in order to understand something, one must first understand the person concerned with the thing. So, ...

Big data has grown rapidly in all walks of life, and many organizations have been forced to look for new and creative ways to manage and control such a large amount of data, not only to manage and control data, but to analyze and tap the value to facilitate business development. Looking at big data, there have been a lot of disruptive technologies in the past few years, such as Hadoop, Mongdb, Spark, Impala, etc., and understanding these cutting-edge technologies will also help you better grasp the trend of large data development. It is true that in order to understand something, one must first understand the person concerned with the thing. So, ...

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 ...

As the amount of data contained in business transactions continues to increase, service providers are looking for ways to make data management for the public cloud easier. 　　Big data is becoming more and more important, and cloud service providers want to get involved in the Enterprise database field. Research institute IDC predicts that large data will increase at a rate of 60% a year, with structured and unstructured data. Enterprises need to find ways to play the role of these data, and for a long time the database is a very good solution. At present, service providers are introducing more ways to host these databases in public cloud through cloud technology, which will make users ...