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Data and Big Data

Big Data Analytics

Hadoop and Big Data

Hadoop Modules

Hadoop vs Conventional Database

Hadoop is ideally used for applications dealing with petabytes of data RDBMS are a good fit for applications with GigaBytes of data

RDBMS are mainly used for structured data. Well defined schemas and data definitions are mandatory for RDBMS. Hadoop works well with structured and unstructured data

Since Hadoop works mostly with semi-structured or unstructured data, it does not need SQL. Hadoop applications do support SQL as well in various lite versions, but it primarily uses HQL or Hive Query Language. Which is particularly good for Metastore. RDBMS use SQL

Hadoop is fully open source, whilst most RDBMS are licensed

Data and Data objects are stored as key-value pairs in Hadoop whereas as the name suggests in RDBMS, data objects are relational

Hadoop is well suited for data types like Audio, Video, Images, etc. RDBMS goes well with relational data such as commonly found in OLTP

Hadoop Ecosystem

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