Transcript
I'm a senior software engineer, and I'm part of a Java team which is specialized in personalization Ibexa. Ibexa’s personalization engine is a part of the Ibexa product, which could be installed on-premises or as a cloud solution.
The main challenge is the time of response. If you want to serve the end user with some recommendations, you should be fast because the users don't like to wait a few seconds until the results are rendered. You need to understand what the problem is.
We may already have a solution. The customer may just be using the wrong tool for it. So you need to deeply understand what this actually should be the end of it.
The main purpose was not to maintain the infrastructure on our side. We simply don't want to think about supporting all this infrastructure. We simply expect it to be working. We compared multiple providers of the database as a service. Astra DB was the best here for the time of response. Astra is a fully Cassandra API, so you know that it's fully supported with the full features of Cassandra. It's not something that is cut off, and you could only add additional features on it. The result is that we are stable, and the customers are happy because they're receiving their recommendations from us, and it's working.