The exponential growth of Big data is independent of the existence of HadoopBut without this open source software it is difficult, yes not impossible, envision both storage, processing, and extraction of value from big data at low cost.
To analyze Big Data without Hadoop, In other words, take advantage of the strategic advantages that this implies for science and also for institutions in general, it would be necessary to look for another technology that would allow it to be done efficiently. Or maybe we should say better that we should create it, even though it would surely be difficult for it to offer all its advantages.
Not in vain, the Arquitectura Hadoop It has characteristics that are wonderfully adapted to the needs of the Big Data universe, both for storage and to allow file sharing and the opportunity to perform heterogeneous data analysis quickly, flexible, scalable, low cost. and resistant to failures.
The strengths of Hadoop architecture
Hadoop architecture enables efficient analysis of unstructured big data, adding a value to them That can help make strategic decisions, improve production processes, save costs, monitor customer feedback or draw scientific conclusions, Let's say.
It is feasible thanks to its scalable technology, its speed (not in real time, at least not without help, like the one provided by Spark), flexibility, among other strengths. If we have to point out your five main advantages, would be the following:
-
Highly scalable technology: a clusterA cluster is a set of interconnected companies and organizations that operate in the same sector or geographical area, and that collaborate to improve their competitiveness. These groupings allow for the sharing of resources, Knowledge and technologies, fostering innovation and economic growth. Clusters can span a variety of industries, from technology to agriculture, and are fundamental for regional development and job creation.... de Hadoop puede crecer simplemente agregando nuevos nodos. It is not necessary to make adjustments that modify the initial structure. Therefore, allows us easy growth, without being tied to the initial characteristics of the design, making use of dozens of low-cost servers that, a diferencia de la databaseA database is an organized set of information that allows you to store, Manage and retrieve data efficiently. Used in various applications, from enterprise systems to online platforms, Databases can be relational or non-relational. Proper design is critical to optimizing performance and ensuring information integrity, thus facilitating informed decision-making in different contexts.... relacional, they can't climb. Gracias al procesamiento distribuido de MapReduceMapReduce is a programming model designed to efficiently process and generate large data sets. Powered by Google, This approach breaks down work into smaller tasks, which are distributed among multiple nodes in a cluster. Each node processes its part and then the results are combined. This method allows you to scale applications and handle massive volumes of information, being fundamental in the world of Big Data...., files are easily divided into blocks.
-
Low cost storage: Information is not stored at the factory, in rows and columns, as is the case with traditional databases, but Hadoop maps categorized data on hundreds of cheap computers, and this represents a great saving. Only then does it become viable. Opposite case, we could not work with large volumes of data, since the cost would be very high, unaffordable for the vast majority of companies.
-
Flexibility: By increasing the number of nodes in the system, we also gain in storage and processing capacity. At the same time, it is feasible to add or enter new and different data sources (structured, semi-structured and unstructured), while there is the opportunity to adapt accessory tools that work in the Hadoop environment and aid in process design, integration or improve other aspects.
-
Speed: Its low cost, scalability and flexibility will be of little use if the result is not reasonably fast. Fortunately, Hadoop also enables you to run very fast analysis and analysis.
-
Fault tolerant: Hadoop is a technology that facilitates the storage of large volumes of information, which in turn enables you to safely recover data. If a computer crashes, there is always another copy available, making data recovery feasible in the event of failure.
Image source: twobee / FreeDigitalPhotos.net
Related Post:
