Naresh Kumar, a software engineer and enthusiastic blogger, has great interest in programming and new things, and is happy to share technical research results with other developers and programmers. Recently, Naresh wrote about 12 well-known free, open source NoSQL databases, and analyzed the characteristics of these databases. Now that the NoSQL database is becoming more and more popular, I'm here to summarize some of the great, free and open source NoSQL databases. In these databases, MongoDB the top, with considerable ...
Open source code platforms for large data are becoming popular. In the past few months, almost everyone seems to have felt the impact. Low cost, flexibility and applicability to trained personnel are the main reasons for open source prosperity. Hadoop, R, and NoSQL are now the backbone of many of the enterprise's big data policies, whether they use it to manage unstructured data or perform complex statistical analyses. "It's almost impossible to keep up with it: SAP AG recently released a new product, SAP BusinessObjects Predictive analytics, software integration ...
Editor's note: Jay Kreps, a chief engineer from LinkedIn, says that logs exist almost at the time of the computer's creation, and there is a wide range of uses in addition to distributed computing or abstract distributed computing models. In this paper, he describes the principles of the log and the use of the log as a separate service to achieve data integration, real-time data processing and distributed system design. Article content is very dry, worth learning. Here's the original: I joined the LinkedIn company at an exciting time six years ago. From that time ...
Editor's note: Jay Kreps, a chief engineer from LinkedIn, says that logs exist almost at the time of the computer's creation, and there is a wide range of uses in addition to distributed computing or abstract distributed computing models. In this paper, he describes the principles of the log and the use of the log as a separate service to achieve data integration, real-time data processing and distributed system design. Article content is very dry, worth learning. Here's the original: I joined the LinkedIn company at an exciting time six years ago. From that time ...
Initially, the platform, the service vendor, establishes its own market differences based on the language it supports, such as Java or. NET, but in the end they continue to evolve to support multiple languages and, ultimately, the infrastructure that serves to support data storage, messaging, application services, and mobility. The market provides a variety of PAAs for developers. Although it seems that PAAs vendors are very similar, but there are many differences. Consider the types that can be controlled, and if so, developers can configure them on the infrastructure. Ideally, PAAs vendors manage all of the implementation ...
I joined the LinkedIn company at an exciting time six years ago. From that point on, we cracked down on a single, centralized database and started switching to a special distributed System suite. This is an exciting thing: the Distributed graphics database, the distributed search backend, the Hadoop installation, and the first and second generation key value data stores that we build, deploy, and still run until today. The most rewarding thing we've learned from all of this is that the core of many of the things we build contains a simple idea: log. Sometimes ...
I joined the LinkedIn company at an exciting time six years ago. From that point on, we cracked down on a single, centralized database and started switching to a special distributed System suite. This is an exciting thing: the Distributed graphics database, the distributed search backend, the Hadoop installation, and the first and second generation key value data stores that we build, deploy, and still run until today. The most rewarding thing we've learned from all of this is that the core of many of the things we build contains a simple idea: log. Sometimes ...
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