When working with databases, we often encounter rows that lack data. This missing data may result from unknown or inapplicable values, errors during data import or input, or specific calculations involving non-existent values. In such cases, there are two ways to represent missing data: NULLs and empty (or blank) values. While these might seem identical at first glance, they are different and impact essential database operations in distinct ways.

We’re happy to announce that VictoriaMetrics, open source time-series database and monitoring solution, and IHI Terrasun Solutions, a leading energy storage system integrator, have partnered on one of North America’s largest clean energy projects! The Gemini Solar + Storage project, which is carefully situated on less than 5,000 acres, is designed to provide clean energy for up to 10% of Nevada’s electricity needs during peak use times.

Managing databases is a real pain point for businesses. It is time-consuming and complicated, and it often distracts resources away from main operations. This is where database as a service (DBaaS) comes into play. DBaaS is revolutionizing the way organizations manage their data—tremendously faster and in a much more secure manner. It is a cloud-native solution that manages your database problems. You no longer have to build and maintain your own database infrastructure.

Oracle Cloud Infrastructure (OCI) provides a robust, versatile platform for modern cloud deployments, catering to businesses with diverse needs, like multi-region scalability, high customization, and hybrid cloud integration. However, the complexity of its architecture and the sheer volume of data generated can present unique challenges in effectively monitoring it.

Long-running queries in MySQL can significantly impact the performance and availability of your database. They can consume server resources, lock tables, and block other queries, leading to cascading performance issues. In this blog, we will explore why long-running queries occur, how to detect them, and best practices for managing and optimizing them.

Choosing a database is no easy feat. You must consider your organization’s current requirements and anticipate its future needs. Also, there are plenty of databases to choose from, and each type has its pros, cons, and use cases. To help you decide, we’re diving into a MongoDB vs. MySQL comparison in this article. We’ll review each database to help you decide which one might meet your needs.

If you're new to working with data, you might have heard of databases and data warehouses. But do you know what sets them apart? Knowing the differences between data warehouses and databases can clear up a lot of confusion for many people, especially with the volume of data we have these days. In this blog post, I'll discuss the differences between these two types of data systems. I'll also provide some examples to help illustrate the points made.

If picking the best database management system (DBMS) were a road trip, both MongoDB and DynamoDB would get you there. Ultimately, it comes down to choosing whether you need the specialized efficiency of DynamoDB within Amazon Web Services (AWS) or the “off-road” flexibility of platform-agnostic MongoDB. What do road trips and off-road antics have to do with deciding between MongoDB vs. DynamoDB?

Learn how to optimize your database for high traffic, ensuring performance, scalability, and reliability under heavy load.