What are the Differences Between Redshift and MySQL

Amazon Redshift is a petabyte-scale Cloud-based Data Warehouse service. It is optimized for datasets ranging from a hundred gigabytes to a petabyte can effectively analyze all your data by allowing you to leverage its seamless integration support for Business Intelligence tools.

MySQL, on the other hand, is a Relational Database Management System. This open-source tool is one of the best RDBMS available in the market that is being used to develop web-based software applications. 

This article discusses the Redshift MySQL comparison to give you an idea about them in detail based on 8 key factors. This would help you make an educated decision when picking a tool tailored to your needs

Understanding Redshift MySQL Differences

• So far in this article, you have seen the features and benefits of Amazon Redshift and MySQL.
• To understand, which tool would suit you better, you can consider the following 8 factors. The factors to keep in mind to understand the Redshift MySQL differences are as follows:

Purpose

• Amazon Redshift is a large-scale Data Warehouse service offered by Amazon that helps serve as the single source of truth for carrying out an insightful analysis using Business Intelligence tools.
• MySQL on the other hand is an open-source Relational Database Management System developed by Oracle.
• MySQL is most widely used for the backend operations of website development due to its affinity for PHP. Amazon Redshift is implemented in the C language while MySQL is implemented in C and C++ languages.

You can also check our article on how to move your data from MySQL to Redshift.

Scalability

• When you compare MySQL and Amazon Redshift in terms of scalability then MySQL is more suited to effectively load small volumes of data more frequently.
• Amazon Redshift, on the other hand, can load large volumes of data less frequently with greater efficiency. 

Performance

• In terms of performance, Amazon Redshift beats MySQL by a large margin with an impressive query time, especially when data is compressed.
• Redshift’s compression saved up to 60% of disk space which firmly establishes a dominant profile for Amazon Redshift.  

OS Support

• When considering Server Operating Systems as a factor for Redshift MySQL comparison, Amazon Redshift is a hosted solution.
• MySQL, on the other hand, supports Linux, OS X, Windows, Solaris, and FreeBSD. 

Cloud Support

• Amazon Redshift is a Cloud-based Data Warehousing tool. MySQL was developed for all use cases.

XML and API

• Amazon Redshift offers no XML support to the users. MySQL on the other hand does offer XML support on its services.
• Amazon Redshift gives you swift querying abilities over Structured data utilizing familiar SQL-based clients, Business Intelligence tools, and standard JDBC and ODBC connections. MySQL uses ADO.NET and Native API along with JDBC and ODBC connections. 

Security

• MySQL protects your data with authentication services, secure connections, data encryption, and fine-grained controls and authorization.
• Amazon Redshift offers a multitude of features to protect your data such as Cluster Security Groups, SSL Connections, Load Data Encryption, VPCs, and Column-level Access Control to name a few.  

Pricing

• MySQL is an open-source tool which means you don’t have to pay for this service. However, you do need to pay for the services of Amazon Redshift.
• Amazon Redshift offers different types of nodes to accommodate your workloads.
• You can choose from DC2 or RA3 based on data size, growth, and required performance.
• The RA3 nodes allow you to optimize your Data Warehouse by paying and scaling for compute and managed storage independently.
• DC2 nodes can be utilized when you have compute-intensive Data Warehouses with local SSD storage to deal with.
• DS2 nodes can be put to use when you need to create large Data Warehouses using Hard Disk Drives (HDD). Here are the pricing plans offered by Amazon Redshift:

Conclusion

1. This article gives you an idea about the factors to keep in mind for Redshift MySQL comparison. It also explores the basics of the two tools, highlighting the features and benefits of each.
2. Extracting complex data from a diverse set of data sources to carry out an insightful analysis can be challenging, and this is where Hevo saves the day!