roapi VS pocketbase

If your use case is read-only I suggest taking a look at roapi[1]. It supports multiple read frontends (GraphQL, SQL, REST) and many backends like SQLite, JSON, google sheets, MySQL, etc.

[1] https://github.com/roapi/roapi

For smaller datasets then anywhere up to a few mb which isn't so bad reasonable with an API but in theory for historic data it could be up to several gb. I've not seen datasette go that high (IIRC it's a 1000 row return limit by default).

That's what got me intrigued with Atlassians offering, as data lakes tend to be something internal to a company, not something I've ever seen offered as an interaction point to users.

I've also tested out roapi [1] which is nice if the data is in some structured format already (Parquet/JSON)

[1] https://github.com/roapi/roapi

https://github.com/roapi/roapi/issues/103?

Very cool and well executed project. Love the sprinkle of Rust in all the other companion projects as well :)

The ROAPI(https://github.com/roapi/roapi) project I built also happened to support a similar feature set, i.e. to expose sqlite through a variety of remote query interfaces including pg wire protocols, rest apis and graphqls.

> why not just accept SQL and cut out all the unnecessary mapping?

You might be interested in what we're building: Seafowl, a database designed for running analytical SQL queries straight from the user's browser, with HTTP CDN-friendly caching [0]. It's a second iteration of the Splitgraph DDN [1] which we built on top of PostgreSQL (Seafowl is much faster for this use case, since it's based on Apache DataFusion + Parquet).

The tradeoff for allowing the client to run any SQL vs a limited API is that PostgREST-style queries have a fairly predictable and low overhead, but aren't as powerful as fully-fledged SQL with aggregations, joins, window functions and CTEs, which have their uses in interactive dashboards to reduce the amount of data that has to be processed on the client.

There's also ROAPI [2] which is a read-only SQL API that you can deploy in front of a database / other data source (though in case of using databases as a data source, it's only for tables that fit in memory).

[0] https://seafowl.io/

[1] https://www.splitgraph.com/connect

[2] https://github.com/roapi/roapi

It could be the NDJSON parser (DF source: [0]) or could be a variety of other factors. Looking at the ROAPI release archive [1], it doesn't ship with the definitive `columnq` binary from your comment, so it could also have something to do with compilation-time flags.

FWIW, we use the Parquet format with DataFusion and get very good speeds similar to DuckDB [2], e.g. 1.5s to run a more complex aggregation query `SELECT date_trunc('month', tpep_pickup_datetime) AS month, COUNT(*) AS total_trips, SUM(total_amount) FROM tripdata GROUP BY 1 ORDER BY 1 ASC)` on a 55M row subset of NY Taxi trip data.

[0]: https://github.com/apache/arrow-datafusion/blob/master/dataf...

[1]: https://github.com/roapi/roapi/releases/tag/roapi-v0.8.0

[2]: https://observablehq.com/@seafowl/benchmarks

It's an obvious question, but have you looked into Pocketbase?

https://github.com/pocketbase/pocketbase

I'd like to plug PocketBase [0] for a similar use case.

Last week I was looking for a place to store random data with API access, and was looking at making a Google Sheets backend, but PocketBase was easy and didn't have a 60 rpm quota.

Deploying to a cheap VPS was very easy with CapRover.

[0] https://pocketbase.io/

What is Pocketbase? Pocketbase is an open-source backend solution offering a real-time database, file storage, and seamless user authentication with OAuth integration, all readily available right out of the box.

Browsing HN, GitHub and the like we get to see a huge variety of software products and code bases.

I often see products and think - if this product X, got together with Y, it would be pretty cool - kind of like if they had a kid together.

Not too literally, but more on the conceptual level - my level of programming is low.

E.g. Just some....

- pocketable.io & datasette (+with some more charting) [https://pocketbase.io, https://datasette.io]

I'm working on a personal project and found myself looking for an alternative to Postman/Insomnia this morning. This made me realize i've been using the same tools for so long for work (mobile development, finance) that this project may be a good time to try out some new things.

Here are a few tools that i've been using lately that I really enjoy:

https://pocketbase.io/ - A dead-simple self-hosted firebase/supabase-like "backend in a box" using golang and sqlite. So far i've been really impressed. I've gone the route of extending the base offering with more go code and am really enjoying the experience.

https://excalidraw.com/ - An open source whiteboarding tool. Slick to use and after learning some keybinds I've gotten pretty fast at throwing together diagrams to explain things to people on my team. The killer piece though is that the filetype is just json, so I can source control my diagrams. Even better, their "export to png" function has a box to embed the json data _into_ the png, allowing me to slap the diagram in places that only accept images (think confluence) and still be able to change the diagram later if needed. 10/10.

https://docs.gitlab.com/ee/ci/ - Gitlab's CI/CD toolset is really impressive, and I've gotten really intimate with it's deeper features over the past year. I'd be curious though to hear from someone who's familiar with it vs it's competitors.

Is there an article somewhere, outside of the Pocketbase docs, presenting that pattern?

- https://github.com/pocketbase/pocketbase/blob/master/core/ap...