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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.

Slow database queries drag down performance for both developers and users. They waste resources, slow down testing, and frustrate customers with laggy experiences. But often, there’s a surprisingly simple fix: indexing. Here’s how indexing works and when to use it, regardless of your schema.

This article will be useful for those who have already installed PostgreSQL on personal computers. In case you still haven’t, this blog post will come in handy. Now, we will focus on the most popular ways of accessing the PostgreSQL database on Windows. We will describe the PostgreSQL connection options using psql, pgAdmin, and fast and convenient dbForge Studio for PostgreSQL by Devart. Moreover, here you will find the instructions on connecting to local and remote PostgreSQL servers.

vmstorage is the component in VictoriaMetrics that handles long-term storage of monitoring data. It receives data from vminsert, organizes the data into efficient storage structures, and manages how long data is kept. Before vminsert even sees the data, agents are out there collecting it, these agents gather metrics from different sources, hold onto the data briefly, and then send it over to vminsert in batches.