MySQL Document Store is a JSON document storage solution built on MySQL. One of the advantages of using MySQL Document Store for JSON document storage is when we need to run complex queries for analytics or reporting we can use raw SQL to retrieve data from our JSON documents. But what if we want to view basic aggregate data, such as average, minimum, maximum, etc.? Can we get that data while still using the Document Store API? Yes, we can, and in this post, we will show you how it can be done.
In a previous post, we talked about how you can view the underlying queries that are run when we make calls to the MySQL Document Store API. While this solution works well on a local or other on-premise instance of MySQL, it is not a viable option for viewing those same queries on a MySQL Database Service (MDS) instance running in Oracle Cloud Infrastructure (OCI). We are going to talk about how to view those queries in MDS.
MySQL Database Service (MDS) is a fully-managed Oracle Cloud Infrastructure (OCI) service that allows you to harness the ease and power of MySQL in the cloud. Since MDS is deployed to OCI, we can take advantage of OCI Alarms to send notifications when a MySQL instance enters a state that is, shall we say, less than favorable. In this post, we will show how to set up an MDS instance and configure an alarm to send an email when the server becomes unavailable.
MySQL HeatWave Database is a fully managed service on Oracle Cloud Infrastructure (OCI) that is developed, managed, and supported by the MySQL team at Oracle. When you provision a new MySQL instance under OCI, you can only connect to the database from inside the OCI network. While this is a great security feature for production services hosted in OCI, it is more challenging to share a development database among different developers. In this post, we will show how you can create a Network Load Balancer to allow access to a MySQL HeatWave Database instance over the internet.
MySQL Document Store is a ‘NoSQL’ solution built on top of MySQL. Last month, I gave a talk at THAT Conference about using MySQL Document Store with Node.js. During that talk, one of the attendees asked if it was possible to see the underlying queries executed when we use the CRUD API in Document Store.
Database indexes are used to help query performance. Database indexes typically contain information about data in a specific column of the database table. With the introduction of functional indexes in MySQL 8.0.13, we can now create indexes based on the result of an expression or function.
Storing JSON in a relational database is something developers have done for quite some time. There are a variety of reasons why you would want to store JSON in a database table - user preferences and configuration data are two good examples. The JSON Data Type was introduced to MySQL in version 5.7.8. This data type allows us to store valid JSON in a database column and run queries based on the values in the JSON.
MySQL Shell is a powerful way to connect to and manage MySQL instances. Connections can even be made to servers that are behind an SSH connection. In this post, we will discuss how to extend and customize MySQL Shell so that it is easier to initiate those connections.
MySQL Document Store is a JSON document storage solution built on top of MySQL. One feature of MySQL Document Store that can help speed up searches is the ability to create indexes of data contained within our JSON documents. In this post, we will demonstrate creating an index and look at the changes made to our collection after we create the index.