This page provides you with instructions on how to extract data from MariaDB and load it into Amazon S3. (If this manual process sounds onerous, check out Stitch, which can do all the heavy lifting for you in just a few clicks.)
What is MariaDB?
MariaDB is a binary drop-in compatible version of MySQL that was created by the original developers of MySQL. It's an open source relational DBMS that supports a rich ecosystem of storage engines and plugins.
What is S3?
Amazon S3 (Simple Storage Service) provides cloud-based object storage through a web service interface. You can use S3 to store and retrieve any amount of data, at any time, from anywhere on the web. S3 objects, which may be structured in any way, are stored in resources called buckets.
Getting data out of MariaDB
MariaDB provides several methods for extracting data; the one you use may depend upon your needs and skill set.
The most common way to get data out of any database is simply to write queries. SELECT queries allow you to pull the data you want. You can specifying filters and ordering, and limit results.
If you're looking to export data in bulk, there's an easier alternative. MariaDB includes a handy command-line tool called mysqldump that allows you to export entire tables and databases in a format you specify, including delimited text, CSV, or an SQL query that would restore the database if run.
Loading data into Amazon S3
To upload files you must first create an S3 bucket. Once you have a bucket you can add an object to it. An object can be any kind of file: a text file, data file, photo, or anything else. You can optionally compress or encrypt the files before you load them.
Keeping MariaDB data up to date
The script you have now should satisfy all your data needs for MariaDB – right? Not yet. How do you load new or updated data? It's not a good idea to replicate all of your data each time you have updated records. That process would be painfully slow; if latency is important to you, it's not a viable option.
Instead, you can identify some key fields that your script can use to bookmark its progression through the data, and pick up where it left off as it looks for updated data. Auto-incrementing fields such as updated_at or created_at work best for this. When you've built in this functionality, you can set up your script as a cron job or continuous loop to get new data as it appears in MariaDB.
Other data warehouse options
S3 is great, but sometimes you want a more structured repository that can serve as a basis for BI reports and data analytics — in short, a data warehouse. Some folks choose to go with Amazon Redshift, Google BigQuery, PostgreSQL, Snowflake, Microsoft Azure Synapse Analytics, or Panoply, which are RDBMSes that use similar SQL syntax. If you're interested in seeing the relevant steps for loading data into one of these platforms, check out To Redshift, To BigQuery, To Postgres, To Snowflake, To Azure Synapse Analytics, and To Panoply.
Easier and faster alternatives
If all this sounds a bit overwhelming, don’t be alarmed. If you have all the skills necessary to go through this process, chances are building and maintaining a script like this isn’t a very high-leverage use of your time.
Thankfully, products like Stitch were built to move data from MariaDB to Amazon S3 automatically. With just a few clicks, Stitch starts extracting your MariaDB data, structuring it in a way that's optimized for analysis, and inserting that data into your Amazon S3 data warehouse.