prql VS rfcs

> I completely attribute this to SQL being difficult or "backwards" to parse. I mean backwards in the way that in SQL you start with what you want first (the SELECT) rather than what you have and widdling it down.

> The turning point for me was to just accept SQL for what it is.

Or just write PRQL and compile it to SQL

https://github.com/PRQL/prql

Hey HN! We’ve built Pretzel, an open-source data exploration and visualization tool that runs fully in the browser and can handle large files (200 MB CSV on my 8gb MacBook air is snappy). It’s also reactive - so if, for example, you change a filter, all the data transform blocks after it re-evaluate automatically. You can try it here: https://pretzelai.github.io/ (static hosted webpage) or see a demo video here: https://www.youtube.com/watch?v=73wNEun_L7w

You can play with the demo CSV that’s pre-loaded (GitHub data of text-editor adjacent projects) or upload your own CSV/XLSX file. The tool runs fully in-browser—you can disconnect from the internet once the website loads—so feel free to use sensitive data if you like.

Here’s how it works: You upload a CSV file and then, explore your data as a series of successive data transforms and plots. For example, you might: (1) Remove some columns; (2) Apply some filters (remove nulls, remove outliers, restrict time range etc); (3) Do a pivot (i.e, a group-by but fancier); (4) Plot a chart; (5) Download the chart and the the transformed data. See screenshot: https://imgur.com/a/qO4yURI

In the UI, each transform step appears as a “Block”. You can always see the result of the full transform in a table on the right. The transform blocks are editable - for instance in the example above, you can go to step 2, change some filters and the reactivity will take care of re-computing all the cells that follow, including the charts.

We wanted Pretzel to run locally in the browser and be extremely performant on large files. So, we parse CSVs with the fastest CSV parser (uDSV: https://github.com/leeoniya/uDSV) and use DuckDB-Wasm (https://github.com/duckdb/duckdb-wasm) to do all the heavy lifting of processing the data. We also wanted to allow for chained data transformations where each new block operates on the result of the previous block. For this, we’re using PRQL (https://prql-lang.org/) since it maps 1-1 with chained data transform blocks - each block maps to a chunk of PRQL which when combined, describes the full data transform chain. (PRQL doesn’t support DuckDB’s Pivot statement though so we had to make some CTE based hacks).

There’s also an AI block: This is the only (optional) feature that requires an internet connection but we’re working on adding local model support via Ollama. For now, you can use your own OpenAI API key or use an AI server we provide (GPT4 proxy; it’s loaded with a few credits), specify a transform in plain english and get back the SQL for the transform which you can edit.

Our roadmap includes allowing API calls to create new columns; support for an SQL block with nice autocomplete features, and a Python block (using Pyodide to run Python in the browser) on the results of the data transforms, much like a jupyter notebook.

There’s two of us and we’ve only spent about a week coding this and fixing major bugs so there are still some bugs to iron out. We’d love for you to try this and to get your feedback!

> Looks like PRQL doesn't have a Go library so I guess they just really wanted something in Go?

There's some C bindings and the example in the README shows integration with Go:

https://github.com/PRQL/prql/tree/main/prqlc/bindings/prqlc-...

Can someone tell me why PRQL is better? I went here: https://github.com/PRQL/prql

It looks nice, but what's the strengths compared to SQL?

PRQL [1] is a compile-to-SQL relational querying language that puts FROM first.

[1] https://prql-lang.org

https://prql-lang.org/ might be an answer for this. As a cross-database pipelined language, it would allow RAG to be intermixed with the query, and the syntax may(?) be more reliable to generate

Search it is! I could implement search that searches for exact tokens in the tools the author connected and the README, but I want to wait for anything more until EdgeDB releases its full-text search solution https://github.com/edgedb/rfcs/blob/master/text/1015-full-te...

I actually had a feature in mind where people could vote on starters they want and others could build them out and list them for free or a price. Do you think that would fit your needs and is there anything in particular you'd want to see in a feature like that?

Replied on Twitter!

> I see EdgeDB as primarily focused on transactional queries, whereas PRQL is very focused on analytical queries.

That's true to an extent currently, but we actually envisioned EdgeQL to be a capable analytical query language too. We'll release EdgeDB 2.0 in a couple of weeks and it will feature a powerful GROUP BY statement (read more about it here [1]) and in 3.0 we might ship window functions (or some equivalent).

With all that said PRQL looks cool!

[1] https://github.com/edgedb/rfcs/blob/master/text/1009-group.r...

>> We shall do better than SQL

> The EdgeQL language looks cool, and I'm sure querying via a graph structure makes certain problems easier in some use cases. However as much as people have complained about SQL, it's just so ubiquitous there needs to be a very good reason to switch away from it. Not having to write joins isn't really a good enough reason, in my opinion.

Oh, it goes much deeper than not writing joins. There's no single ORM out there that can implement a TypeScript query builder like ours, see the example in [1]. This is only possible because of EdgeQL composability, but that composability required us to rethink the entire relational foundation.

> > The true source of truth

> I'm not sure why this means EdgeDB is better. <..>

This section implies that EdgeDB's schema allows to specify a lot of meta / dynamically computed information in it. And soon your access control policies. Take a look at the work-in-progress RFC [2] [3] to see how this is more powerful, then say, Postgres' row level security.

> > Not just a database server

> It sounds like they have a solid client, which is awesome.

Also lightweight connections to the DB so that you can have thousands of concurrent ones without load balancers, built-in schema migrations engine, and many other things. In fact we have so much that it's challenging what to even highlight in a blog post like the 1.0 announcement.

> Cloud-ready database APIs

> This used to be true, but is definitely no longer true. Cloud-native databases are everywhere and incredibly common. See any major cloud, https://www.cockroachlabs.com/, or any of the tons of other database solutions.

Not to pick on CockroachDB (they have an amazing product and company, we love them), but you should benchmark local install of Postgres and Cockroach to see yourself that scalability still has a significant cost in performance.

[1] https://www.edgedb.com/blog/edgedb-1-0#not-just-a-database-s...

[2] https://github.com/edgedb/rfcs/pull/49

[3] https://github.com/edgedb/rfcs/pull/50/files

EdgeQL is getting support for generic partitioning/aggregating `GROUP` very soon [1], so we are giving some love to the analytical side of things too :-)

We definitely need more collective effort put into "Better SQL", so PRQL is a welcome sight!

[1] https://github.com/edgedb/rfcs/blob/21e581a188715c6ff82944b6...