When the services in your distributed application interact with a database, you need telemetry that gives you end-to-end visibility into query performance to troubleshoot application issues. But often there are obstacles: application developers don’t have visibility into the database or its infrastructure, and database administrators (DBAs) can’t attribute the database load to specific services.

Amazon’s Relational Database Service (Amazon RDS) offers a variety of database instances, which can be confusing at first. In this guide, we'll clarify what each RDS instance class, family, type, and size means in under 15 minutes. Let's start at the beginning.

With the release of SQL Sentry 2023.3, I look back at the past 18 years I have worked with the product to admire where it is today versus then. It’s been an incredible experience with a lot of moving parts, but no matter what market forces or acquisitions happen along the way, the core intention of “Improving the lives of Microsoft DBAs everywhere” has stayed the same. This is a two-part blog post: below, I’ll talk about our history and where we’ve come from.

When you're building a serverless web app, it can be pretty easy to forget about the database. You build a backend, send some data to a frontend, write some tests, and it'll scale to infinity with no effort, right? Not quite. Especially not with a tiny Postgres server. As the number of users of your frontend increases, your app will open more and more database connections until the database is unable to accept any more. That's just the frontend - it gets worse on the backend.

This month, I celebrate 11 years of working on SQL Sentry. I started as employee number 15 at SentryOne and then moved through various roles in support, customer success, and professional services to my current role as product manager. In an industry where innovation and adaptation are key, the journey of SQL Sentry and its team has been remarkable. SQL Sentry has come a long way since its early days.

Amazon RDS or Relational Database Service is a collection of managed services offered by Amazon Web Services that simplify the processing of setting up, operating, and scaling relational databases on the AWS cloud. It is a fully managed service that provides highly scalable, cost-effective, and efficient database deployment.

In our previous article about Database migrations we explained why you should treat your databases with the same respect as your application source code. Database migrations should be fully automated and handled in a similar manner to applications (including history, rollbacks, traceability etc).

With the huge growth in volume and complexity, data management has become a key priority in most Enterprises. But for this data to be utilised in a meaningful way, how do you tackle the added complexity of controlling access across both technical and business departments? Our CPO, David Gummer recently interviewed the CEO of the popular Universal Database management tool, DBeaver, Tatiana Krupenya, to discuss the often-feared topic of sharing access to the database. Prefer video? Watch the interview here.

Azure SQL is a versatile and powerful database service, and it is an increasingly popular choice for storing and managing application data due to its scalability, high availability, security, and simplicity of integration. A common demand for cloud workloads is cost optimization. To maximize cloud savings, this article discusses Azure SQL Database Cost Optimization.