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Hadoop > Learn Hadoop > What is the difference between big data and Hadoop?
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What is the difference between big data and Hadoop?

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Hadoop is a framework for storing and processing big data, while big data is a term used to describe large and complex data sets that are difficult to process using traditional methods. Hadoop can be used to process big data by dividing it into smaller blocks that can be processed in parallel.
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"Transforming your struggles into success"

**Big Data** refers to extremely large and complex data sets that traditional data processing tools cannot handle efficiently. It includes structured, semi-structured, and unstructured data, characterized by high volume, velocity, and variety. **Hadoop** is an open-source framework specifically designed...
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**Big Data** refers to extremely large and complex data sets that traditional data processing tools cannot handle efficiently. It includes structured, semi-structured, and unstructured data, characterized by high volume, velocity, and variety.

 

**Hadoop** is an open-source framework specifically designed to store and process big data across distributed clusters of computers. It provides tools like HDFS for storage and MapReduce for processing, making it a key solution for handling big data.

 

**Key Difference**: Big Data is the problem of handling massive datasets, while Hadoop is one of the technologies designed to solve that problem.

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