Deployment Guide
This section contains guides, best practices and advices related to deploying and managing Cube.js in production.
Below you can find guides for popular deployment environments:
- Docker
- AWS Serverless
- GCP Serverless
- Heroku
- Cube Cloud
https://cube.dev/docs/deployment/guide
This section contains guides, best practices and advices related to deploying and managing Cube.js in production.
Below you can find guides for popular deployment environments:
- Docker
- AWS Serverless
- GCP Serverless
- Heroku
- Cube Cloud
https://cube.dev/docs/deployment/guide
cube.dev
Deployment Guide | Cube.js Docs
Documentation for working with Cube.js, the open-source analytics framework.
GitHub - cube-js/cube.js: 📊 Cube.js — Open-Source Analytical API Platform
https://github.com/cube-js/cube.js
https://github.com/cube-js/cube.js
GitHub
GitHub - cube-js/cube: 📊 Cube Core is open-source semantic layer and LookML alternative for AI, BI and embedded analytics
📊 Cube Core is open-source semantic layer and LookML alternative for AI, BI and embedded analytics - cube-js/cube
Getting Started with Cube.js using Docker | Cube.js Docs
https://cube.dev/docs/getting-started/docker
https://cube.dev/docs/getting-started/docker
cube.dev
Getting Started with Cube using Docker | Cube Docs
Getting Started with Cube using Docker | Documentation for working with Cube, the open-source analytics framework
Getting Started with Cube.js using Docker | Cube.js Docs
https://cube.dev/docs/getting-started/docker
https://cube.dev/docs/getting-started/docker
cube.dev
Getting Started with Cube using Docker | Cube Docs
Getting Started with Cube using Docker | Documentation for working with Cube, the open-source analytics framework
At Cube Dev, we are building a technology stack for modern analytics and our mission is to make it accessible to developers around the world.
We are focused on bottom-up adoption, and most of our software is open-source. Cube.js, our flagship open-source product, has over 10,000 stars on GitHub and over 3,000 community members in Slack. It powers companies ranging from Apple, Intel, and Walmart to small Silicon Valley startups.
Our business model is based on Cube Cloud, our paid enterprise cloud platform that helps deploy, optimize, and scale Cube.js apps. It's in early access while serving dozens of enterprise customers already. Cube Cloud will also have a free tier for our open-source users.
We are a 15-person remote-first team distributed over the US, UK, and Eastern Europe with an HQ in San Francisco, funded by top-tier Silicon Valley venture funds that have previously invested in Redis, Hazelcast, Gradle, and other infrastructure software startups.
Cube.js is used to build analytical APIs over trillion data point datasets in SQL databases (e.g., Postgres, ClickHouse) and data warehouses (e.g., Google BigQuery, AWS Athena, Snowflake). Such APIs serve requests with sub-second latency and high concurrency.
Cube Cloud provides observability, reliability, and scalability for Cube.js applications. It helps enterprise customers run, monitor, and auto-scale Cube.js deployments under strict SLAs while decreasing time-to-market and reducing costs. Cube Cloud pairs with Cube.js just like BigQuery pairs with Google Cloud Platform or MongoDB Atlas pairs with MongoDB.
We're determined to further enhance Cube Cloud and make it generally available later this year. That's why we're looking for a technical lead to join the Cube Cloud team. You will contribute to Cube Cloud, help our enterprise customers succeed, serve as an entry point for the team, and work with our CTO to drive architectural and product decisions.
During the first months, you'll be working on these features:
Cube.js APM. One of the main tech problems for Cube Cloud is to provide application performance monitoring analytics of Cube.js instances using Cube.js itself. Being purely a dogfooding problem, large-scale real-time analytics has a lot of challenges, most of which will be solved for the first time ever using the SQL approach.
Cube Cloud PaaS Infrastructure. Cube Cloud provides a platform as a service infrastructure to deploy Cube.js applications in production capacity at scale. Being based on AWS, GCP, Azure and other cloud providers it's a sophisticated cloud in cloud implementation with a lot of various infrastructure challenges.
Cube Store Service. Cube.js is used to serve analytics for trillions of data points with sub-second response times. To keep up-to-date with growing big data demands and serving speeds we’re developing our own database optimized for serving huge aggregated tables with latencies of several milliseconds. On-demand Cube Store service provides access to hundreds of cores for several milliseconds per query that allows processing terabytes of rollup rows.
We are focused on bottom-up adoption, and most of our software is open-source. Cube.js, our flagship open-source product, has over 10,000 stars on GitHub and over 3,000 community members in Slack. It powers companies ranging from Apple, Intel, and Walmart to small Silicon Valley startups.
Our business model is based on Cube Cloud, our paid enterprise cloud platform that helps deploy, optimize, and scale Cube.js apps. It's in early access while serving dozens of enterprise customers already. Cube Cloud will also have a free tier for our open-source users.
We are a 15-person remote-first team distributed over the US, UK, and Eastern Europe with an HQ in San Francisco, funded by top-tier Silicon Valley venture funds that have previously invested in Redis, Hazelcast, Gradle, and other infrastructure software startups.
Cube.js is used to build analytical APIs over trillion data point datasets in SQL databases (e.g., Postgres, ClickHouse) and data warehouses (e.g., Google BigQuery, AWS Athena, Snowflake). Such APIs serve requests with sub-second latency and high concurrency.
Cube Cloud provides observability, reliability, and scalability for Cube.js applications. It helps enterprise customers run, monitor, and auto-scale Cube.js deployments under strict SLAs while decreasing time-to-market and reducing costs. Cube Cloud pairs with Cube.js just like BigQuery pairs with Google Cloud Platform or MongoDB Atlas pairs with MongoDB.
We're determined to further enhance Cube Cloud and make it generally available later this year. That's why we're looking for a technical lead to join the Cube Cloud team. You will contribute to Cube Cloud, help our enterprise customers succeed, serve as an entry point for the team, and work with our CTO to drive architectural and product decisions.
During the first months, you'll be working on these features:
Cube.js APM. One of the main tech problems for Cube Cloud is to provide application performance monitoring analytics of Cube.js instances using Cube.js itself. Being purely a dogfooding problem, large-scale real-time analytics has a lot of challenges, most of which will be solved for the first time ever using the SQL approach.
Cube Cloud PaaS Infrastructure. Cube Cloud provides a platform as a service infrastructure to deploy Cube.js applications in production capacity at scale. Being based on AWS, GCP, Azure and other cloud providers it's a sophisticated cloud in cloud implementation with a lot of various infrastructure challenges.
Cube Store Service. Cube.js is used to serve analytics for trillions of data points with sub-second response times. To keep up-to-date with growing big data demands and serving speeds we’re developing our own database optimized for serving huge aggregated tables with latencies of several milliseconds. On-demand Cube Store service provides access to hundreds of cores for several milliseconds per query that allows processing terabytes of rollup rows.
React Pivot Table with AG Grid and Cube.js 🔢 - DEV Community
https://react-pivot-table.cube.dev/
https://react-pivot-table.cube.dev/
Performance capabilities of data warehouses and how Cube can help - Cube Blog
https://cube.dev/blog/data-warehouse-performance-and-how-cube-can-help/
https://cube.dev/blog/data-warehouse-performance-and-how-cube-can-help/
Cube Blog
Performance capabilities of data warehouses and how Cube can help - Cube Blog
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.
Building an Appsmith Dashboard with Cube - Cube Blog
https://cube.dev/blog/building-an-appsmith-dashboard-with-cube
https://cube.dev/blog/building-an-appsmith-dashboard-with-cube
Cube Blog
Building an Appsmith Dashboard with Cube - Cube Blog
In this article, I want to create a statistics dashboard with Appsmith. I'll use API endpoints generated from Cube that uses a public dataset from the Museum of Modern Art (MoMA).