pavel_tiunov

You actually can use any npm packages. Here's an example on how you can use `node-fetch`: https://cube.dev/docs/schema/advanced/dynamic-schema-creatio.... Same capabilities are coming soon for Python and YAML as well.

Yep. Cube would automatically figure out the join path for you on top of the defined join graph in the data model using the Dijkstra algorithm. The best practice however is to use views: https://cube.dev/docs/schema/reference/view/#views. Those can be used to explicitly control join paths and get an effect similar to what Looker Explore can provide.

https://cube.dev/docs/config/downstream might be a great starting point for that. Here you can get a grasp of how dashboard apps can be built: https://cube.dev/docs/examples#tutorials-front-end-integrati.... Here's the post about embedding into Next.js app in particular: https://cube.dev/blog/building-nextjs-dashboard-with-dynamic....

Nice catch! This one is typo for sure :) Thanks!

Showplow is great and cost effective. AWS Cloudfront, Lambda and Athena make it possible to create fully serverless setup on top of it. There's an open source example of such setup: https://statsbotco.github.io/cubejs/event-analytics/

It actually works exactly as you describe. We generate SQL query to return aggregates based on SQL supplied in Cube.js schema. We never fetch raw data from SQL backend. Architecture overview can probably help to understand: https://github.com/statsbotco/cubejs-client#architecture

Thanks for the question! We should do a better job describing this. In short: 1. Generates analytic SQL queries based on Cube.js schema. It can be simple ones like calculating page views or more advanced like calculating session metrics, attribution models or funnels. 2. Caches sql responses to not to overwhelm SQL backend with user requests. 3. Pre-aggregates data to be able to query trillions of data points in matter of seconds. 4. Orchestrates SQL query execution. Organizes dependencies between pre-aggregations, queue priorities, cache refreshes. 5. Provides REST analytic API for end users.

Yes. I guess your setup is serverless as well. Big Query is one of Serverless MPP databases that shares similar concepts with AWS Athena.

Hi Alex, Great thanks for your feedback! We're about to implement app configuration API to use by other declarative RAD languages like yours. Please reach us in our Gitter chat or by any other convenient way (https://allcountjs.com/community) so we could discuss how can we be helpful.

Yep. Exactly!

Hi h3rald, Nice job! Does it allow to persist different fields? Or the main purpose is to save unstructured documents?

Hi willyr! Thanks for your question! I'm co-founder of AllcountJS. It's relatively new framework. We recently finished 4 real world projects using it and pushed them to production already. If you interested please join our Gitter chat where we can discuss it in detail: https://gitter.im/allcount/allcountjs