postgres VS prql

I want to use this as a chance to bring attention to a GitHub issue that I think would help reduce friction for Neon:

https://github.com/neondatabase/neon/issues/4989

If the Neon driver were to allow us to easily pass in a localhost connection, the development and test experience would be easier. Perhaps Neon could swap to something like this internally: https://github.com/porsager/postgres.

Having run a local dev environment connected to Neon and tests connected to Neon got in our way of adoption. We'd prefer to develop and run tests against a regular Postgres localhost database.

To the PMs of Neon, put yourself in the shoes of a new developer thinking of giving Neon a try. What changes will I have to make to my code and my development workflow?

I'd push you to consider using postgres, slonik or similar for database queries. With these libraries, you just write SQL, but they perform input sanitization for you. So you can safely write:

Thanks Pier! Your comment saved me some frustration here :-D

https://github.com/porsager/postgres/discussions/627#discuss...

There's a core client interface here:

- https://www.postgresql.org/docs/current/client-interfaces.ht...

On what makes it postgres.js faster, from author himself:

> it seems Postgres.js is actually faster than, not only pg, but of any driver out-there

- https://github.com/porsager/postgres/discussions/627

- https://porsager.github.io/imdbench/sql.html

When viewed as a DSL for set theory, views, CTEs, set-returning functions, et al are indeed proper first-class query abstractions.

When viewed through the lens of general purpose imperative or functional programming languages, it's easy to see how it can be seen as falling short.

I'll admit much of the tooling and driver APIs leave a lot to be desired.

Some tools do make good efforts though such as nested fragments in this driver.

https://github.com/porsager/postgres#building-queries

I don't think this should turn in to an ORM or not debate, but there are plenty of reasons, especially for the crowd that would do anything to avoid ORMs. Just try to take a peek into the multitude of "ORMs are bad" articles / discussions.

For instance - I would love to be able to use https://github.com/porsager/postgres with sqlite.

Demonstrate how easily and accidentally one can make an SQL injection with these:

https://github.com/porsager/postgres

https://github.com/gajus/slonik

They've looked at Postgres.js (https://github.com/porsager/postgres) before — wouldn't mind if they enabled those other cases in the same way.

> 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