In conjunction with Postgres for related relational data, I’m using timescale for IoT based time series data.
Is this something I’d use instead of timescale, or, am I understanding that the intention here is to be a data warehouse, where we could potentially offload older data to Arc for longer term storage or trend analysis?
I’d say both roles are possible, though the original intent of Arc was indeed to act as an offload / long-term store for systems like TimescaleDB, InfluxDB, Kafka, etc. The idea: you send data into Arc to reduce storage and query load on your primary database for ML, deep analysis, etc.
But as we built it, we discovered that Arc is really good not just at storage but at actively answering queries, so it’s kind of hybrid: somewhat “warehouse-like,” but still retaining database qualities in performance. I feel that saying a database its too much, but we are going on that direction.
IoT is absolutely one of the core use cases. You’re often ingesting tens or hundreds of thousands of events per second from edge devices, and you need a system that doesn’t choke. Our binary MessagePack ingestion helps shrink the payload size and reduce parsing overhead, that allows higher throughput for writes, which is crucial in IoT scenarios.
Let me know if you want to explore this a little more, not for selling you anything, at least not yet, I would love to understand your use case. Let me know if you are open: ignacio[at]basekick[dot]net
No, you can ask arbitrary queries. I’ve found that foundation models (and Claude in particular) do a great job at writing sql. It even seems to handle time series questions pretty well.
Could Gemini CLI be used for PR reviews? For example, would you expect that asking Gemini to compare two git commit hashes and analyze the code changes for potential bugs/conciseness/adhesion to the idiomatic project style, etc. to work well?
Edit: I tried it. The setup was a breeze. I fed the CLI two git commit IDs and some light prompting on what to look for. It gave a reasonable response. I'll try on a real PR shortly.
I would have loved to see such a list when I joined a startup. I'm not sure it's possible to make a comprehensive list, given all the various startup structures and agreements, but still a "top 10" list with some guidance on how to protect yourself would be valuable.
Or... an SLM where you feed the model your contract and it provides a list with recommendations tailored to your situation.
I hold no judgement here, as someone who has only ever built software for profit but if the intention is to make it OSS, why not start that way? For many, OSS is a core feature, and as you know, many devs have been burned by postman, insomnia, etc.
To the best of my understanding, it is exactly what I wrote in the parent comment. It's the fact that the core lacks bits developed in the internal tool but not yet unglued from what will go in the plugins section.
It's not unheard of. For instance, I got another team and devtool I work with, non-related to the API niche, and they are going open source mid-next week. Some teams want to build the core their way, some want to see if it will catch traction before committing to support an entire community and contributions, some have got something else going on, some actually ARE shady and talk OSS for clout, etc.
>There used to be a business in selling these ultra performant ST chips to high frequency traders, who'd overclock the absolute crap out of them. Luckily, this is no longer a business.
* Testing prompt behavior across various LLMs
* Sharing those prompts across multiple applications
We currently use a jupyter notebook to iterate, test, and validate prompts. Then move those prompts to our production app written in C#. If there were a C# SDK, I could use this tool to create a prompts config file and share it between the jupyter notebook and the C# app. The config file could also be added to version control.
Having said that, I don't understand why it saves the output of the LLM so maybe I'm missing something.
> It's yet another sign the standard of living is declining for the young.
Or maybe a reflection of higher expectations? Housing, healthcare, and vehicles are all examples of things that both cost more and are much more advanced than the same version previous generations had.
Also young people are living in cities more than previous generations and those cities are denser. The value prop of a car, price aside is less than it was for previous generations.
The economic value of a location changes over time, so the land component of the house is not the same. Plus increases in population can dramatically shift supply and demand curves.
Sure, but basically all desirable places to live now are expensive, which wasn't the case before.
I'm not sure about the exact causes, but at some level it has to be supply and demand, I agree. Maybe just growing population. Certainly the bay area is, in my opinion, very over-populated.
It's a magical physical location, and there's too many people that want to live in it, for it to be pleasant.
(Though the horrible government also isn't helping.)
Eh, I feel eBay has more of a right to ban books than a library. Both are bad, and it’s terrible that society is in a place where book banning is virtuous.
I don't necessarily think eBay should be forced with legal might to sell these books -- but it's a terribly bad look for their company. Book banning has always felt scummy to me, and I always think back to being a child when many in my community participated in Harry Potter book burning events. Book burning, witch burning, it's all mob mentality and it's terrifying.
Is this something I’d use instead of timescale, or, am I understanding that the intention here is to be a data warehouse, where we could potentially offload older data to Arc for longer term storage or trend analysis?