hackathon-starter VS cube.js

Well, I've never attended a Hackerthon before and have no prior knowledge of what it looks like. But I happen to come across a guide that we'll help me start up when the time comes. The Hackerthon starter will help you set up a NodeJS application and will help you focus on what is really important. This starter also provides you with a boilerplate that features local authentication with email and password, authentication via Twitter, Facebook, Google, GitHub, LinkedIn, and Instagram, flash notifications, MVC project structure, account management, API examples, and much more to help you get started.

A few years ago, I built the website https://sea-air-towers.herokuapp.com/ whose code is at https://github.com/JohnReedLOL/TypeScript-Node-Starter . It's a site that helps people who annualy rent units in this beachfront vacation condo building find other units in the same building to rent next year (my mom is president of the building and asked me, with my bachelor's in Computer Science, to build the site for her). I built it by forking and then building on top of the TypeScript Node.js starter seed application code at https://github.com/microsoft/TypeScript-Node-Starter . I chose this TypeScript seed because I prefer TypeScript over JavaScript due to the types and the JavaScript seed (that the TypeScipt seed which I chose was based on) which is at https://github.com/sahat/hackathon-starter has a ton of stars on GitHub, so I assumed it was a good seed for building a site. The thing is, looking back, I wonder if maybe WordPress would have been a better tool to build this site. Two questions:

If you're not sure what you want to do maybe build your own sample site from a "starter" like https://github.com/microsoft/TypeScript-Node-Starter (this one uses TypeScript which is JavaScript with types added) or https://github.com/sahat/hackathon-starter (this one uses plain old JavaScript without types). I personally deploy to https://www.heroku.com/ because it's less complicated than deploying to AWS or Google Cloud but more businesses deploy to AWS than Heroku so learning AWS and having the AWS services you use to build and deploy your app as skills on your resume would probably make your resume look better to companies than just saying you know Heroku. If you want to copy off me (don't make and use an exact copy) my sample app deployed to Heroku has its code at https://github.com/JohnReedLOL/TypeScript-Node-Starter and the site is at https://sea-air-towers.herokuapp.com/ (I pay Heroku $7 a month for hosting). It's good to have a link to a sample app and link to the code for your sample app on your resume, just make the README.md file on GitHub look good so people can look at it and know what your app does. I have a software library with a much better looking README.md file at https://github.com/JohnReedLOL/pos

I can't see your application, but in general when I want to build my own application from scratch I build it by adding stuff to a "starter" or "seed application" like https://github.com/sahat/hackathon-starter . That seed application runs on a backend JavaScript server called Node.js which you would have to learn, there are books on Node.js on Amazon and also playlists on places like YouTube, Udemy, and Coursera. For deployment of small apps like apps built from that starter I like to use an online service called "Heroku". You need to know how to use the command line and a code management and version control tool called "git" that hooks into a website called GitHub where code like the code for that seed application is hosted. There's a big learning curve. There are other tools and methods that you can use. For example there is a thing called "WordPress" that can be used to build websites with PHP on the backend instead of JavaScript. WordPress has a drag-and-drop user interface builder. WordPress is used a lot for small businesses like little stores that sell stuff online. If you're an individual making a personal web page there are no-code, drag-and-drop personal web page builders like Wix and SquareSpace, but those pages are more for showing off static content than providing any interactive functionality. I think Amazon Web Services and Microsft Azure Cloud also offer low-code simple app building services for apps that aren't meant to look good or be super customized. Without knowing the details of your app, how it looks like or is supposed to look like, and what exactly you want to create, I don't know which approach is best for you.

authentication is when you provide credentials to a system IOT verify you are who you claim you are, local means not remote, i.e your computer and not a network. this is NOT how git operates out of the box so far as I can see, as evidenced by what i posted in the post you're replying to. this may be a language barrier thing, perhaps read here if you want to learn more about these concepts

3. Node.js Hackathon Starter

heres a good one i use a lot these days https://github.com/sahat/hackathon-starter

I'm a little rusty as I've been on disability for 3 years, but before that I worked as a backend programmer for Amazon and gotten a bachelor's in computer science. Maybe we can build a web app together and host it on Heroku or AWS, I think maybe we can use https://github.com/sahat/hackathon-starter to get started and build off that. Or maybe you come up with something yourself or we build on one of your projects. We can put the project on GitHub and add it to our resumes to show off to prospective employers. Leave a comment or send me a chat request and we can work together.

When building a web app from scratch, I recommend you build on top of a hackathon starter like https://github.com/sahat/hackathon-starter or maybe https://github.com/microsoft/TypeScript-Node-Starter if you want to use TypeScript, but for your purposes I believe you don't need TypeScript. The starter includes all the dependencies you need and you can pretty easily host it on something like Heroku or AWS.

Try a new tool with starters: For example, if you want to try to use express to build your web page, and you know nothing about it. In the beginning it can be very frustrating if you are struggling with the basics or syntax or debugging stuffs. You can try a starter which has coded the structure for you and you just need to fill things in. (Hackathon starter - A kickstarter for Node.js web applications)

I should have clarified. There's a large number of apps that are:

1. taking info strictly from SQL (e.g. information_schema, query history)

2. taking a user input / question

3. writing SQL to answer that question

An app like this is what I call "text-to-sql". Totally agree a better system would pull in additional documentation (which is what we're doing), but I'd no longer consider it "text-to-sql". In our case, we're not even directly writing SQL, but rather generating semantic layer queries (i.e. https://cube.dev/).

I'm not too familiar with https://cube.dev/ - but my initial impression is they are focused more on providing APIs backed by SQL. They have a SQL API that emulates the PostgreSQL wire protocol, whereas Spice implements Arrow and Flight SQL natively. Their pre-aggregations are a similar concept to Spice's data accelerators. It also looks like they have their own query language, whereas Spice is native SQL as well.

Hey HN!

Over the past year, my co-founder David and I have been building Delphi to let developers create amazing customer-facing AI experiences on top of their data. We're excited to share it with you.

David and I have spent our careers leading data and engineering teams. After ChatGPT got popular, we saw a rush of "chat with your data" startups launch. Most of these are "text-to-SQL" and use an LLM like GPT-4 to generate SQL queries that run directly against a data warehouse or database.

However, the general perception now is most of them make for nice demos but are hard to make work in the real world. The reason is data complexity. Even smart LLMs find it difficult to reason about messy databases with hundreds of tables, thousands of columns, and complex schemas that have been built up piece-meal for years. Text-to-SQL can be a fine dev tool for data scientists and analysts, but we've seen many organizations hesitate to deploy it to end users, who never know if the answer they get one day will be the same the next.

David and I found a better way. From our time in the data engineering world, we were familiar with a type of tool called "semantic layers." Think of them like an ORM for analytics. Basically, they sit between databases (or data warehouses) and data consumers (data viz tools like Tableau or APIs) and map real-world concepts (entities like "customers" and metrics like "sales") to database tables and calculations.

Semantic layers are often used for "embedded analytics" (e.g. when you're building customer-facing dashboards into your application) but are increasingly also used for traditional business intelligence. Cube (https://cube.dev) is a prominent example, and dbt has also recently released one. They're useful because with a semantic layer, the consumer doesn't have to think about questions like "how do we define revenue?" when running a query. They just get consistent, governed data definitions across their business.

We realized that semantic layers could be just as useful for LLMs as for humans. After all, LLMs are built on natural language, so a system that deterministically translates natural language concepts into code has obvious power when you're working with LLMs. With a semantic layer, we've found that companies can get AI to answer much more complex questions than without it.

For a year now, we've been building Delphi to do just that. We've gone through a few iterations/pivots (initially we were focused on building a Slack bot for internal analytics) and are now seeing our developer-first approach resonate. We're being used to power customer-facing fintech applications, recruiting software, and more.

How do you use Delphi? The first step is connecting your database; then, we build your semantic layer on top of it. Right now we do this manually, but we're moving more and more of it over to AI. Once that's done, we have 3 main ways of using Delphi: 1) white-labeling our AI analytics platform and providing it to your customers; 2) a streaming REST API and SDKs; and 3) React components to easily drop a "chat with your data" experience into your app.

If this is interesting to you, drop us a line at [email protected] or sign up at our website (https://delphihq.com) to get in touch. Thanks for reading! Would love to hear any thoughts and feedback.

We use https://cube.dev/ as intermediate layer between data warehouse database and Superset (and other "terminal" apps for BI like report generators). You define your schema (metrics, dimensions, joins, calculated metrics etc) in cube and then access them by any tool that can connect to SQL db

also check out cube.dev. they can do the semantic layer and cache it so you are not hitting Snowflake all the time.

We need metrics to live in source control with reviews. Metabase doesn't have a git integration for metrics, which is why we are convinced to use cube.dev as a semantic layer.

https://github.com/cube-js/cube comes out very well at the end as a promising open source system, getting rather close to the bullseye. Would love to know more & hear people's experience with it.

How is this different from something like https://cube.dev/

Have a look to cube.js

For now, I've been thinking on using self-hosted Rudderstack both for ingestion and reverse ETL, cube.dev as the abstraction later for building webapps and providing catching for the BI layer, and dbt for transformations. But I have doubts with the following elements: