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Databases

Load Testing SQL Databases with k6

This short tutorial shows how to run a k6 test for load testing a database. In performance testing, we often trigger load tests that simulate realistic user flows, particularly those that are most commonly seen in production. This type of acceptance testing usually interacts with various parts of our infrastructure: web servers, microservices, databases, etc. But what if you want to test the performance or scalability of an infrastructure resource in isolation?

Get a Complete View of Salesforce Data with MongoDB

Teri will show you how you can incorporate Salesforce (relational data) into a MongoDB collection (non-relational data) to give your customers a unified customer experience. The webinar will focus on the piece of the puzzle where we read Salesforce data and format it into the shape needed to go into a Mongo collection (a collection is the term MongoDB uses for a data set like a table in a relational database). We’re showcasing the ability to go back and forth from NoSQL to SQL for a unified customer experience.

Scalable event streaming with Redis and Golang

A common problem that our customers have is event streaming spikey traffic to their clients. For example, imagine a server which needs to stream details on cryptocurrency trades. The quantity of trades happening each second is likely to fluctuate, sometimes nothing could happen, other times perhaps thousands. In order to ensure reliable communication, it’s important that rate limits are in place on how many messages are to be sent to subscribed clients.

MongoDB vs. MySQL: Detailed Comparison of Performance and Speed

MongoDB and MySQL are similar is some ways, but they also have some obvious differences. Perhaps the most obvious one is that MongoDB is a NoSQL database, while MySQL only responds to commands written in SQL. Potential users may want to examine MongoDB vs. MySQL in the areas of performance and speed. The following article will help you understand the differences, as well as the pros and cons of each database.