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What is the differences between RDBMS Data Warehouse and big data Hadoop?

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Unlike RDBMS, Hadoop is not a database, but rather a distributed file system that can store and process a massive amount of data clusters across computers. However, RDBMS is a structured database approach in which data is stored in rows and columns which can be updated with SQL and presented in different...
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Unlike RDBMS, Hadoop is not a database, but rather a distributed file system that can store and process a massive amount of data clusters across computers.

However, RDBMS is a structured database approach in which data is stored in rows and columns which can be updated with SQL and presented in different tables.

read less
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My teaching experience 12 years

Unlike RDBMS, Hadoop is not a database, but rather a distributed file system that can store and process a massive amount of data clusters across computers. However, RDBMS is a structured database approach in which data is stored in rows and columns which can be updated with SQL and presented in different...
read more
Unlike RDBMS, Hadoop is not a database, but rather a distributed file system that can store and process a massive amount of data clusters across computers. However, RDBMS is a structured database approach in which data is stored in rows and columns which can be updated with SQL and presented in different tables. read less
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"Transforming your struggles into success"

Unlike RDBMS, Hadoop is not a database, but rather a distributed file system that can store and process a massive amount of data clusters across computers. However, RDBMS is a structured database approach in which data is stored in rows and columns which can be updated with SQL and presented in different...
read more

Unlike RDBMS, Hadoop is not a database, but rather a distributed file system that can store and process a massive amount of data clusters across computers. However, RDBMS is a structured database approach in which data is stored in rows and columns which can be updated with SQL and presented in different tables.

read less
Comments

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**RDBMS:** - Structured data - Fixed schema - ACID compliance - Suitable for transaction processing **Data Warehouse:** - Centralized repository - Optimized for query and analysis - Historical data storage - Often uses ETL processes **Hadoop:** - Handles structured and unstructured data -...
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**RDBMS:** - Structured data - Fixed schema - ACID compliance - Suitable for transaction processing **Data Warehouse:** - Centralized repository - Optimized for query and analysis - Historical data storage - Often uses ETL processes **Hadoop:** - Handles structured and unstructured data - Flexible schema (schema-on-read) - Scalable and distributed - Ideal for large datasets and batch processing read less
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