Posted on

Cloud Data Warehouse Comparison: Redshift vs. BigQuery vs. Azure vs. Snowflake for Real-Time Workloads

Data helps companies take the guesswork out of decision-making. Teams can use data-driven evidence to decide which products to build, which features to add, and which growth initiatives to pursue. And, such insights-driven businesses grow at an annual rate of over 30%.

But, there’s a difference between being merely data-aware and insights-driven. Discovering insights requires finding a way to analyze data in near real-time, which is where cloud data warehouses play a vital role. As scalable repositories of data, warehouses allow businesses to find insights by storing and analyzing huge amounts of structured and semi-structured data.

Posted on

How to Use Backendless With React.js: Real-Time Database Integration Tutorial

This is the third part of our series on using Backendless with a React.js frontend app. You can catch up on the previous articles here: Part 1 and Part 2. If you'd like to jump in now, you can simply create a new Backendless app, clone our previous progress from our repository, and use this commit as an entry point for today's article.

Our goal for today is to showcase integration with our Real-Time (we call it RT) database for delivering changes in your data table from the server to the client. We have previously written about implementation of RT in an Angular app ( "How to Use the Backendless Real-Time Database in Your Angular App"). If you're interested in Angular or you just want to see difference between the usage of RT with React and Angular, we'd recommend you give that article a read.