Reliability: Hadoop utilizes distributed storage and processing, with data replicated across multiple nodes, ensuring data reliability and fault tolerance.
Scalability: Hadoop can easily expand to hundreds or thousands of servers to process massive amounts of data.
High performance: Hadoop utilizes the MapReduce parallel computing model to efficiently process large-scale data.
Usability: Hadoop offers simple and easy-to-use APIs and tools, allowing developers to easily develop and manage big data applications.
Open source: Hadoop is freely available and can be customized and extended based on individual needs.
The ecosystem of Hadoop is diverse, with various tools and technologies like Hive, Pig, HBase, etc., which make it easy to build complex big data applications.
Support for multiple data types: Hadoop can handle various types of data, including structured data, semi-structured data, and unstructured data.