Tips, Expertise, Articles and Advice from the Pro's for Your Website or Blog to Succeed
I like counting stars. Especially stars on GitHub! Tracking the growth of popular GitHub repositories has always been interesting to me. That's why I decided to use the public data set of GitHub events in ClickHouse to create dashboards with actionable metrics.
In this tutorial, I'll explain how to build a custom front-end visualization that fetches data from a ClickHouse instance. I'll use a managed instance of ClickHouse from Altinity Cloud and Cube Cloud as the metrics API layer.
Cube has been an open-source project since 2018. We try our best to listen to the community and our users to make it the best analytics API server on the market today.
We really appreciate all the help and sincere dedication our lovely community has done to provide feedback, submit pull requests, and feature ideas to improve Cube even more. We hope the soon-to-be 12,000 stars on GitHub are a representation of our dedication to making our community happy.
You're bound to have heard the term GraphQL. Unless you live under a rock. I doubt that though. GraphQL is a query language for APIs and a runtime for fulfilling those queries with your existing data.
This tutorial will show you a step-by-step guide on how to use a GraphQL API to build Postgres metrics dashboards.
Have you ever been asked to build a metrics dashboard for displaying internal performance metrics like HTTP response times? Maybe even showing metrics for something business-related like new users visiting a landing page every day?
Don't you love it!?
Don't you really hate latency? Yeah, I hate it too.
Today, I want to talk about building applications on top of data warehouses. I want to discuss how to achieve low latency if your app is consuming data from BigQuery, Snowflake, Redshift, or any other cloud-based data warehouse.