Last May, KubeCon gathered multiple tech enthusiasts, students, professionals, and companies. The event highlighted various topics and insights on how to collaborate on pushing the boundaries of cloud-native computin One of our Engineering Directors, Mykola Marzhan, shared his knowledge about databases on Kubernetes at KubeCon, during a session organised by the DoK.Community. We’ve picked out some of the key highlights from the talk below.

IT leaders, engineers, and developers must consider multiple factors when using a database. There are scores of open source and proprietary databases available, and each offers distinct value to organisations. They can be divided into two primary categories: SQL (relational database) and NoSQL (non-relational database). This article will explore the difference between SQL and NoSQL and which option is best for your use case.

In the previous blog, SQL vs NoSQL Database, we discussed the difference between two major database categories. In a nutshell, the main difference between NoSQL and SQL is that NoSQL adopts a ‘right tool for the job’ approach, whilst SQL adopts a ‘one tool for all the jobs’.

When I started at Grafana in January, I was accustomed to working with private clouds and on-prem infrastructure, so nearly everything in my role here as a senior software engineer for the Grafana Mimir customer squad was new to me. I was new to Golang, Docker, Kubernetes, gRPC, public cloud services, etc. Kubernetes has been especially challenging. In my work on Grafana Mimir and Grafana Enterprise Metrics, I experience k8s in one of two extremes.

We've simultaneously launched 4 new integrations for Node.js: Redis, ioredis, MySQL, and MySQL2. This means that you can now see all the details of a query in the Event Timeline and Slow Query screens in AppSignal. Because we are a small and bootstrapped team, we've chosen to embrace OpenTelemetry as a means of expanding AppSignal's offering in the Node.js ecosystem.

For over a decade, Amazon RDS (Relational Database Service) has been a popular managed database service companies have used to set up, operate, and scale databases for web and mobile applications. However, modern, high-scale applications can have upward of tens of thousands of clients. This means that maintaining direct connections between the database and application can quickly begin to consume more resources than the query executions themselves.

I was recently joined by Chris Yates, Senior Vice President, Managing Director of Data and Architecture at Republic Bank for our webinar, Gain the competitive edge with a monitoring tool. The session sparked an insightful conversation around estate monitoring from the perspective of a Senior VP, and I wanted to share some of the key take-aways.

Today’s developers use tools such as VMware Tanzu Application Platform and the Spring framework to build modern applications. However, to build best-of-breed, intelligent, data-centric applications, developers must utilize a unified, in-memory data layer. This enables development teams to truly scale their applications with the pace of business, especially when that business extends across the globe.

PlanetScale is a serverless, MySQL-compatible database platform powered by Vitess. PlanetScale handles database scaling while also providing you with the tools to increase your development velocity, such as branching, non-blocking schema changes, automatic backups, built-in connection pooling, as well as a helpful interface and CLI. Datadog’s new integration gives you deep visibility into your PlanetScale databases, so you can optimize your usage and costs.