I recently started my new pet-project using ExpressJS as a backend API server, so it’s a good time to document each step and help node.js newcomers to start building real things using this great technology.
I plan to write a series of posts about databases internals. In order to make it easily perceivable, I’ll be writing a NoSQL DB from scratch in Ruby. No doubts that it’s not the best fit for database development, but it’s extremely readable and will help us a lot. This one will be about why may you want to have an index and what is a Hash index.
UPD. I decided to not continue this series because it takes too much effort to investigate deep enough to explain, but it had got much fewer views and likes than more applicable ones. Probably will return to this topic once, but not now.
Today I gave a talk on Ruby User Group Berlin meetup, here is a recap of it in a readable format.
In my team, we are building a new and fast-evolving SPA product. We are small in terms of a number of developers and we are agile in terms of the market. We test the design of an idea, quickly implement it, test it with real users, then either keep and improve or change or remove. Quite a quick pace, so when we were choosing the web framework we wanted it to be more a helper for us rather than a box, out of which we cannot step.
If you followed my 3 my previous posts – you already created your first Amazon Lambda function, made it able to write to DynamoDB and be accessible from the outside world, using API Gateway.
In this post, I will guide you how to implement the same but without touching the AWS Management Console, which is barely understandable and very volatile by the interface. Instead, we will be using Terraform, which I also covered in the past blog post.
Let’s get started:
In this post, we will create a Lambda function which can write to the Amazon DynamoDB table. For this, we will create a table, modify existing function and set up IAM roles. Log in to your AWS account and let’s get started!
This post is the second one in series about Amazon Web Services first steps howtos.
I believe that traditional guides like AWS Certification preparation and Linux Academy don’t give the information in proper order, so here I give it in the format and the way how I give it to my colleagues at Babbel.
This post gives you an introduction to the DynamoDB and prepares a ground for the next practical lesson.
I just started AWS Learning Sessions in the company, I’m currently working in, and want to share with you our first lesson.
We have built small Lambda function, named Greeter, and integrated it to the AWS API Gateway.
If you want to get started with this tools and get some hands-on experience – this article will help you.
Hey folks! Today we will try to find some text in our collection. And then we will add text indexes there and behold, how it become better (or not). Let’s grab a beer and start.
Hello boys and girls, looking forward to know more about MongoDB indexes?
Today we’ll talk about Multikey indexes. Yeah, only about them because it’s quite a big topic. I also wanted to cover text indexes, but they are too cool to talk about them in the same post, they deserve their own %)
So let’s start!
As you may know, PostgreSQL provides you four index types: B-tree, Hash, GiST and GIN. They all named the way that if you don’t know ’em you’ll never get which one do you need. In MongoDB indexes are named in a more human-readable way. Here they are:
1. Single field index.
2. Compound index.
3. Multikey index.
4. Text index.
5. Hashed index.
6. 2dsphere, 2d, geoHaystack indexes.
Since I’m using Mongo for more than a year now, I worked with few of them and will elucidate you the most commonly used ones.