When it comes to data storage, there is almost as much diversity in the types of databases as there is in the data that they contain. Designing and implementing a strong enterprise data strategy means that you need to be aware of the different databases and how you might best apply them within your organization. In IT, the term "flat file" means something very different from the heavy-duty steel construction file cabinets that you might buy from Safco.

MongoDB is a popular non-relational (a.k.a NoSQL) database. It is document-oriented and distributed in nature. MongoDB is known to be highly scalable and flexible. In this post, we'll demonstrate how you can utilize MongoDB in your ETL pipelines with Xplenty. To start with, let us briefly discuss why and when you'd want to use MongoDB over other relational databases.

Optimizing server performance is important in supporting end-user requirements. Using server optimization, actively monitor: Web server monitoring and optimization helps you to troubleshoot bottlenecks as they emerge and optimize server performance. In this post, we will discuss how to optimize performance and why it is important.

Database replication for database analytics involves many serious difficulties.

In today’s post, we’ll dive into how we, at AppSignal, solved a daunting engineering challenge. Giving you a look into the kitchen, this post will show you how we tested a new database in production without having to worry about errors/downtime. Alright, let’s get cooking!

How do you integrate data from Amazon RDS (Relational Database Service) with data from other sources such as S3, Redshift, or even MongoDB? The answer is Xplenty. Our data integration on the cloud lets you join data from various sources and then process it to gain new insights. What about storing the results back to RDS? No problem; Xplenty does that as well.

Here’s how to choose a relational database for your next project.

Regardless of the tech stack used, many developers have already used Redis or, at least, heard of it. Redis is specifically known for providing distributed caching mechanisms for cluster-based applications. While this is true, it’s not its only purpose. Redis is a powerful and versatile in-memory database. Powerful because it is incredibly super fast. Versatile because it can handle caching, database-like features, session management, real-time analytics, event streaming, etc.

Companies these days are handling more data than ever: an average of 163 terabytes (163,000 gigabytes), according to a survey by IDG. Efficiently storing, processing and analyzing this data is essential in order to glean valuable insights and make informed business decisions. Yet the question remains: What is the best way to store enterprise data? For many use cases, the most appealing choice is a relational database.