Introduction to Amazon RedShift and its use cases

In this recipe, we will learn about Amazon RedShift. We will also learn about the use cases of Amazon RedShift.

Recipe Objective - Introduction to Amazon RedShift and its use cases?

The Amazon Redshift is widely used and is defined as a data warehouse product that forms part of the larger cloud-computing platform Amazon Web Services, red being an allusion to Oracle, whose corporate colour is red and is informally referred to as "Big Red. Amazon Redshift is built on top of technology from the massive parallel processing (MPP) data warehouse company ParAccel which was later acquired by Actian for handling large scale data sets and database migrations. Amazon Redshift differs from Amazon's other hosted database offering, Amazon RDS, in its ability to handle analytic workloads on big data sets stored by the column-oriented DBMS principle. Further, Amazon Redshift allows up to 16 petabytes of data on a cluster compared to Amazon RDS's maximum database size of 16TB. The Amazon Redshift is based on an older version of PostgreSQL (version 8.0.2), and Redshift has made changes to that version. An initial preview beta was released in November 2012 and further a full release was made available on February 15, 2013. The service is allowed to handle connections from most other applications using ODBC and JDBC connections. Amazon Redshift has the largest Cloud data warehouse deployments, with more than 6,500 deployments as per the Cloud Data Warehouse report published by Forrester in Q4 2018. Amazon Redshift uses parallel processing and compression to decrease command execution time and this allows the Redshift to perform operations on billions of rows at once. This also makes Redshift useful for storing and analyzing large quantities of data from logs or live feeds through a source such as Amazon Kinesis Data Firehose.

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Benefits of Amazon Redshift

  • The Amazon Redshift can be used to set up SSL to secure data in transit, and hardware-accelerated AES-256 encryption for data at rest If the user chooses to enable encryption of data at rest, all data are written to disk will be encrypted as well as any backups thus Amazon Redshift takes care of key management by default and provides End-to-end encryption. Amazon Redshift lets you configure firewall rules to control network access to user's data warehouse cluster and users can run Amazon Redshift inside Amazon Virtual Private Cloud (VPC) to isolate the data warehouse cluster in their virtual network and connect it to the existing IT infrastructure using an industry-standard encrypted IPsec VPN and thus provides Network isolation. Amazon Redshift integrates with AWS CloudTrail to enable users to audit all the Redshift API calls and it logs all SQL operations, including connection attempts, queries, and changes to the user's data warehouse. Users can access these logs using SQL queries against system tables, or save the logs to a secure location in Amazon S3. Amazon Redshift is compliant with SOC1, SOC2, SOC3, and PCI DSS Level 1 requirements and thereby providing Audit and compliance.

System Requirements

  • Any Operating System(Mac, Windows, Linux)

This recipe explains Amazon Redshift and Use cases of Amazon Redshift.

Use cases of Amazon Redshift

    • It optimizes the business intelligence

Amazon Redshift enables building the insight-driven reports and dashboards using the Amazon QuickSight, Tableau, Microsoft PowerBI, or other business intelligence tools and thus optimizing the business intelligence.

    • It increases the developer productivity

Amazon Redshift provides simplified data access, ingest, and allows egress from numerous programming languages and platforms without further configuring drivers and managing database connections and thus increasing the developer productivity.

    • It enables collaboration and shares data

Amazon Redshift enables the securely sharing of the data among accounts, organizations, and partners while building applications on top of third-party data and helps in optimizing the business intelligence, thus providing a lot of benefits to its users and further enabling collaboration between users and sharing of data.

    • It improves financial and demand forecasts

Amazon Redshift automatically creates, train, and deploy machine learning models for predictive insights and let them improve the financial and demand forecasts.

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