Big Data storage layer | The Ultimate Course of Big Data Architectures | Mastering Big Data 2023

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The Big Data Storage Layer is a crucial component of any Big Data architecture. It refers to the layer that is responsible for storing large volumes of data in different formats.

There are several types of storage solutions that can be used in a Big Data architecture, each with its own strengths and weaknesses.

Data Lake:
A Data Lake is a large repository that stores all types of structured, semi-structured, and unstructured data in its native format. The purpose of a Data Lake is to provide a central location for storing all of an organization's data, regardless of the data source or format. Data Lakes are highly scalable and can handle large volumes of data. They are often used for advanced analytics and machine learning.

here are some examples OF DATA LAKES:
Apache Hadoop HDFS Hadoop distributed file system


In addition, There are many cloud-based storage options that can be used in a Big Data architecture, such as
Amazon S3
Microsoft Azure Data Lake Storage
Google Cloud Storage


Data Warehouse:
A Data Warehouse is a central repository of structured data from multiple sources, optimized for querying and reporting. Data Warehouses are designed to handle large volumes of structured data and are used for business intelligence and decision-making purposes. Data Warehouses typically require a predefined schema and data modeling before data can be loaded into them.
Data Warehouse:
Amazon Redshift
Apache Hive
Presto
Apache Calcite


Database:
A Database is an organized collection of structured data that can be accessed, managed, and updated through software applications. Databases are used to store and manage structured data, such as customer information or financial data. There are two main types of databases: Relational databases, which store data in tables with predefined schemas, and NoSQL databases, which are designed to handle unstructured or semi-structured data.
Database:
Oracle Database
MySQL
MongoDB
Cassandra


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