Based on the have swept the globe as the most secure. Decentralized form of currency, with no need for a financial institution to function as a middleman. Web-based exchanges regularly create a lot of data for consulting firms because the internet is the only source for trading. This information is open to the public and ready to be used for future investments.
Due to their volume-based nature. While this raises concerns about the legally trading, it is also creating opportunities for enterprises such as:
Analysts of exchanges, and consulting businesses
Their job is to keep track of and analyse exchange rates in order to predict how they will perform in the stock market. Exchange analysts consistently rely on online apps that automatically aggregate data from such exchanges and transform it into useable form in their attempt to scale their business and convert investors into clients. Hire node.js Developer
IndyLogix Solutions Pvt Ltd has had the opportunity to collaborate, a exchange rate analysis organisation comparable. Our work resulted in a SailsJS-based web application that can gather data from 20 various exchanges and build whitelisted market indices to assess the market.
- Creating a NodeJS application with the SailsJS framework
- Using 20 separate third-party services to integrate exchange data
- Obstacles they encountered during the development process
If you want to make a data web application, keep reading to learn about the development procedure for one.
Let’s start with a review of the main features of the web application we created.
Key Features of a Cryptocurrency Data Aggregator
It is necessary to have a basic understanding of a exchange and the data generated from it in order to understand the application’s primary features.
What is the definition of a exchange?
A exchange functions in the same manner as a bank or an airport does with Local currency. You enter and exchange your home money for any other available currency. These trades for online through a web gateway where you may either convert your into another fiat currency
On the internet, there are various exchanges to choose from, including GDAX, Bittrex, CoinEgg, and Binance.
Because each exchange has its own exchange rate, traders find it difficult to determine the market index of currency or which exchange offers the best rates.
What method did we use to obtain currency exchange data?
Using their APIs is the most dependable approach to legally retrieve data. APIs for currency exchanges are widely available since they not only provide data on currency exchange rates but also allow users to make transactions using their API.
We just needed real-time and historical exchange rate data for our use case.
We installed a custom CRON job charged with triggering the data PULL request from the API every couple of minutes because the currency exchange data updates in real-time every few minutes.
Using visuals to whitelist raw exchange data
By computing average exchange data per currency, we may generate our own data sets using the aggregated data. The retrieved information is separated and presented in tabular and chart form:
I Using tabular data to display a list of top based on top performers for to USD exchange, top performers for ultimately a complete list of all cryptocurrencies.
Except for the Charts, all of the columns in the following snapshot are retrieved through the data exchange provider’s API.
- ii) Using Charts to Display Data: To illustrate individual performance, we used two separate chart libraries: C3 Charts and Sparkline charts.
- C3 is number one. Charts were used to show the fluctuation in the price of a exchange rate.
- The TC100 index (price of the top 100 Crypto Currencies by market cap) and how it fluctuated during the day were displayed using Sparkline charts.
Developing a REST API from scratch
Finally, It makes all of the whitelisted market indexes available as a JSON data stream. It gives users access to their database’s data as a JSON feed, allowing them to build a similar platform using any web development framework using data.
Let’s have a look at the technology stack that was employed now that we have a general idea of what features were constructed.
Technology Stack for Data Aggregator
MySQL was used to conduct on the database side.
Why should you choose SailsJS: NodeJS Framework?
SailsJS is one of the few NodeJS frameworks that follows the MVC pattern. We were able to keep the application logic distinct from the user interface code and manage the interactions between them in a separate layer as a result of this.
Furthermore, SailsJS gives the flexibility to switch the storage layer via its Waterline ORM, allowing us to use Mysql and its comprehensive methods for constructing and optimising database queries.
The only reason we chose SailsJS was because of its well-organized development and deployment workflow, which didn’t compromise the application’s performance.
Apart from the fact that EJS is SailsJS’ official template engine, we chose it because of its HTML-based syntax. Despite the fact that we had the option of using more powerful UI frameworks such as Angular or Jade, EJS is the best language for front-end templating in SailsJS.
We were able to jumpstart the front-end development with an off-the-shelf Bootstrap template and were developing controller code to display data in views in no time.
We had to overcome the following obstacles:
1. Maintaining Data Exchange Homogeneity
The Web app was designed to collect data from 20 different trading companies. The difficulty in combining data from multiple sources into a single application is that each data exchange web service has its own vocabulary, data feed format, and calling nature.
Because our front-end views can only receive data in a linear format, this makes the raw data worthless. As a result, retrieving data and saving it in a database is never a simple operation.
To address this obstacle, we began by developing our own array to store the data from all exchanges. We created our own format, which will be used by various views throughout the website.
The For each loop performs the conversion for each variable provided by the exchange web service, and at the conclusion of the Switch case, we get a linear and homogenous custom array of exchange data.
2. Reducing the time it takes for data to load
The previous method of loading the complete exchange data on page load. Never the optimal approach to load the data, as we discovered firsthand. Due to the volume of data loaded on page launch, the web app immediately displayed long loading times.
As a result, by the time the page loaded, the data was almost complete. It only took a few more seconds to fully load the data.
This was more of a time management technique for loading the web application’s content. Resulted in an immediate increase in the application’s loading speed.
We’ve also extended our development efforts for a WordPress plugin that delivers all of the exchange data. unique market indexes as a WordPress widget, using the publicly developed API.
This Node.JS application is as expandable as it gets, thanks to its development in SailsJS, which separates visual entities from core logic. Hire dedicated node.js Developer
Working as development partners, the future promises some great development potential for us. Keep an eye on our blog for updates on the newest developments.