pljs VS llrt

pljs (https://github.com/plv8/pljs) is a postgres language plugin that also uses quickjs. given how much faster the startup is compared to v8, and that most postgres functions are very small and do very little compared to a node.js program, it is quite good.

I can definitely see aws' lambda operations gaining quite a bit from this.

Any plans to add support for? https://github.com/awslabs/llrt

It would also be nice to have a V8/deno/bun based edge hosting option that supports the Next.js edge and middleware code splitting. That's the missing piece for most homebrew "edge" setups. Production CDNs like Clouflare and Supabase all offer this.

Vlad Ionescu: Scaling containers on AWS in 2022 GitHub: awslabs/llrt AWS Documentation: Understanding the Lambda execution environment Amazon Science: How AWS's Firecracker virtual machines work Lumigo GitHub: MiddyJS

Its refreshing to see all the various JS engines that are out there for various usecases.

I have been working on providing quickjs with more node compatible API through llrt [1] for embedding into applications for plugins.

[1] https://github.com/awslabs/llrt

AWS has open-sourced its JavaScript runtime, called LLRT (Low Latency Runtime), an experimental, lightweight JavaScript runtime designed to address the growing demand for fast and efficient Serverless applications.

FROM --platform=arm64 busybox WORKDIR /var/task/ COPY app.mjs ./ ADD https://github.com/awslabs/llrt/releases/latest/download/llrt-container-arm64 /usr/bin/llrt RUN chmod +x /usr/bin/llrt ENV LAMBDA_HANDLER "app.handler" CMD [ "llrt" ]

Let’s get the simplest use case out of the way: cases where the cold starts are so fast that it’s not an issue for you. That’s usually the case for function that use runtimes such as C++, Go, Rust, and LLRT. However, you must follow the best practices and optimizations in every runtime to maintain a low impact cold start.

But compared to other runtimes, LLRT is not so good in terms of performance when it comes to dealing with large data processing, Monte Carlo simulations, or performing tasks with a large number of iterations. The AWS team says that it is best suited for working with smaller Serverless functions dedicated to tasks such as data transformation, real-time processing, AWS service integrations, authorization, validation, etc. Visit the GitHub repository of this project to learn more information.

And lastly, lean into your cloud vendor. Stop trying to build a better mouse trap. Advances in technology are happening all the time. The speed of AWS' Lambda has been rapidly improving over the past couple of years with the launch of things like SnapStart and LLRT