Amazon S3

Storage

Technology

Move data between MySQL and S3 quickly and easily. Import structured cloud data into MySQL. Collect CSV, XML, plaintext, and other data in S3 data lakes for BI and AI analytics. 


Start moving your data quickly with this solution, which includes:
<ul>
<li>Quick steps for setting up your MySQL and Amazon S3 connectors</li>
<li>Methods for moving structured and semi-structured data from MySQL databases to Amazon S3 buckets</li>
<li>Methods for moving structured and semi-structured data from Amazon S3 buckets to MySQL databases</li>
</ul>
Overview:
MySQL is a leading relational database for business and the most popular open source RDBMS in the world. Use it to store structured data on-premises or in the cloud and to make data available for SQL-based queries and analyses.
Amazon S3 buckets are the primary storage technology for Amazon data lakes. Flexible and highly scalable, they provide storage for a wide variety of data types — including CSV, XML, and text — which can be accessed by other applications for artificial intelligence, business intelligence, and other use cases. S3 can also be used for backups and highly affordable long-term archiving..
This solution makes it easy to move data between these two leading data repositories. Set up connectors and quickly move data from your MySQL databases into S3 for analysis alongside other data. Or export S3 data into MySQL for SQL-based storage and reporting..
Take advantage of Amazon S3 buckets for fast, scalable storage to aggregate data from multiple MySQL databases..
Business agility requires working with both structured and unstructured data. Connecting MySQL to Amazon S3 buckets helps bring these two types of data together.