In this article, I will tell you about a-few-years journey of scaling the Elasticsearch cluster in production environment, which is one of the vital elements of the iPrice technology stack.
I will describe challenges we encountered and how we approached them.
In the first part of You don't know Redis, I built an app using Redis as a primary database. For most people, it might sound unusual simply because the key-value data structure seems suboptimal for handling complex data models.
In practice, the choice of a database often depends on the application’s data-access patterns as well as the current and possible future requirements.
Redis was a perfect database for a Q&A board. I described how I took advantage of sorted sets and hashes data types to build features efficiently with less code.
Now I need to extend the Q&A board with registration/login functionality.
I will use Redis again. There are two reasons for that.
Firstly, I want to avoid the extra complexity that comes with adding yet another database.
Secondly, based on the requirements that I have, Redis is suitable for the task.
Important to note, that user registration and login is not always about only email and password handling. Users may have a lot of relations with other data which can grow complex over time.
Despite Redis being suitable for my task, it may not be a good choice for other projects.
Always define what data structure you need now and may need in the future to pick the right database.
As a side hustle, I teach tech recruiters web and software development technologies using plain English. It helps them with understanding job specs and resumes and it makes all of us, tech people, happier.
I run a weekly newsletter and often get feedback from recruiters via email or LinkedIn DMs.
I thought that I could try to collect feedback using the “Reactions” feature just like LinkedIn or Facebook does. It’s not as informative as personalised messages but is a simple feature that may incentivize more people to provide some general feedback.
Either way, it’s worth trying and as a software developer, I can’t wait to implement it.
This tutorial is about implementing a feature that will be used in real life on my project.
Originally posted on DEV.to
In my previous post, I touched on the point that Redis is more than just an in-memory cache.
Most people do not even consider Redis as a primary database. There are a lot of use cases where Redis is a perfect choice for non-cache related tasks.
In this article, I will demonstrate how I built a fully functional Q&A board for asking and upvoting the most interesting questions. Redis will be used as a primary database.
I will use Gatsby (React), Netlify serverless functions and Upstash Serverless Redis.
Upstash has been a good choice so far and I decided to try it out in a more serious project. I love everything serverless and how it makes things simpler for me.
Serverless will be a great choice for most tasks however you need to know the pros and cons of the tech you are using. I encourage you to learn more about serverless to get the most out of it.
Academic data warehouse design recommends keeping everything in a normalized form, with links between. Then the roll forward of changes in relational math will provide a reliable repository with transaction support. Atomicity, Consistency, Isolation, Durability — that's all. In other words, the storage is explicitly built to safely update the data. But it is not optimal for searching, especially with a broad gesture on the tables and fields. We need indices, a lot of indices! Volumes expand, recording slows down. SQL LIKE can not be indexed, and JOIN GROUP BY sends us to meditate in the query planner.
