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.

Azure Synapse (formerly Azure SQL Data Warehouse) is a cloud-based petabyte-scale columnar database service with controls to manage compute and storage resources independently. It offers encryption of data at rest and dynamic data masking to mask sensitive data on the fly, and it integrates with Azure Active Directory. It can replicate to read-only databases in different geographic regions for load balancing and fault tolerance.

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.

Azure Synapse provides a multi-step process for loading data. After extracting the data from its source, you can move it to Azure Blob storage or Azure Data Lake Store. You can then use one of three utilities to load the data:

• AZCopy uses the public internet.
• Azure ExpressRoute routes the data through a dedicated private connection to Azure, bypassing the public internet by using a VPN or point-to-point Ethernet network.
• The Azure Data Factory (ADF) cloud service has a gateway that you can install on your local server, then use to create a pipeline to move data to Azure Storage.

From Azure Storage you can load the data into Azure Synapse staging tables by using Microsoft's PolyBase technology. You can run any transformations you need while the data is in staging, then insert it into production tables. Microsoft offers documentation for the whole process.

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.

Azure Synapse is great, but sometimes you need to optimize for different things when you're choosing a data warehouse. Some folks choose to go with Amazon Redshift, Google BigQuery, PostgreSQL, Snowflake, or Panoply, which are RDBMSes that use similar SQL syntax. Others choose a data lake, like Amazon S3 or Delta Lake on Databricks. 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 Panoply, To S3, and To Delta Lake.