I’ve been building web apps since… well, since before anybody called them web apps. I wrote my first web page in 1992, I was building data-driven dynamic websites in ASP and PHP way back in the 1990s. I’ve seen countless trends and technologies rise, and sometimes fall – from cgi-bin scripts to templating languages, to static site generators and serverless cloud microservices.
Redis is a great choice for implementing a highly available in-memory data structure store, that can be used as a database, cache, and message broker. Combine it with some of its modules, for example, RediSearch and RedisJSON and you get a full-text search engine.
In this post, we’ll dive into building our simple, yet effective and powerful search engine, starting from loading data into Redis, then performing text searches using a rich query language and finally aggregate or group query results to our specific needs.
When we start creating a new application, we should adhere to the basic postulates: that the code we write is simple, easy to test, that it can be maintained, and that it is readable and understandable for the colleagues we work with or to those will subsequently take over maintaining our application. Furthermore, at the very beginning, we should think about how complex the structure of our application is and how we will manage the data we have without our application being fast, user friendly, or reliable.
The idea of creating a digital bank stemmed from the market’s needs. In particular, there is a high demand for faster, easier, more modern and more flexible banking services. Traditional banks are still slow to adapt to the latest technology trends and clients’ demands. Based on our previous experience within the industry, we concluded that most of the clients had the same or similar problems when it comes to using services from traditional banking institutions. That is why we decided to create a flexible digital bank.
