Minimal Learning: Hevo, with its simple and interactive UI, is extremely simple for new customers to work on and perform operations. Schema Management: Hevo takes away the tedious task of schema management & automatically detects the schema of incoming data and maps it to the destination schema. Secure: Hevo has a fault-tolerant architecture that ensures that the data is handled in a secure, consistent manner with zero data loss. The solutions provided are consistent and work with different BI tools as well. Its fault-tolerant and scalable architecture ensure that the data is handled in a secure, consistent manner with zero data loss and supports different forms of data. Its completely automated pipeline offers data to be delivered in real-time without any loss from source to destination. Hevo not only loads the data onto the desired Data Warehouse/destination but also enriches the data and transforms it into an analysis-ready form without having to write a single line of code. It supports 100+ data sources ( including 30+ free data sources) like Asana and is a 3-step process by just selecting the data source, providing valid credentials, and choosing the destination. Hevo Data, a No-code Data Pipeline helps to load data from any data source such as Databases, SaaS applications, Cloud Storage, SDKs, and Streaming Services and simplifies the ETL process. Our focus will be on utilizing REST as an architectural principle in this article. JSON-RPC - JSON Format for Data Transfer. Once the raw data is received, further processing can be performed. 
Likewise, when a system requests Raw Data from an API endpoint, the system receives Raw Data in return. The result of the request will be a Google response, which may contain HTML, CSS, JavaScripts, or other assets consumed by, executed by, and rendered by the user’s system. For example, when users enter a URL into their browser, like they make a GET request to Google’s server. Essentially, it facilitates communication between two software systems. Heroku Flask MongoDB: Setting up HerokuĪPIs are application programming interfaces.Heroku Flask MongoDB: Building the Web API with Flask.Heroku Flask MongoDB: Loading Data in MongoDB.Heroku Flask MongoDB: Building a Database with MongoDB.Heroku Flask MongoDB: Setting up a Git Repository and a Virtual Environment.This article demonstrates how to build a scalable REST API web service using Flask, a very nice Python web microframework paired with MongoDB, the most popular No-SQL database, and Heroku as the deployment platform.īut before we start digging into the details, let’s cover some basics.
Sometimes, it can be challenging to build scalable REST APIs, especially for new developers with limited experience and understanding.
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