Ariosys, Big Data Consulting & Interactive Virtual Training Center

Infrastructure is the foundation of Big Data architecture. Possessing the right tools for storing, processing and analyzing data is critical in any Big Data project.

 

Ariosys could helps you to build Hadoop infrastructure for your Big Data ingestion, analysis and predictive analytics.

 

HADOOP

Key components includes computation and distributed repository:

• HDFS- Distributed repository 

• MapReduce- Executes a wide range of analytic functions by analyzing datasets in parallel before ‘reducing’ the results. The “Map” job distributes a query to different nodes, and the “Reduce” gathers the results and resolves them into a single value.

• YARN- Responsible for cluster management and scheduling user applications

• Spark- Used on top of HDFS, and promises speeds up to 100 times faster than the two-step MapReduce function in certain applications. Allows data to loaded in-memory and queried repeatedly, making it particularly apt for machine learning algorithms

 

NOSQL

NoSQL, which stands for Not Only SQL, is a term used to cover a range of different database technologies, unlike their relational predecessors, NoSQL databases are adept at processing dynamic, semi-structured data with low latency, making them better tailored to a Big Data environment.

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MASSIVELY PARALLEL PROCESSING (MPP)

MPP technologies process massive amounts of data in parallel.