wasmedge-quickjs VS wasmedge-db-examples

I'm impressed you're already leveraging the component model. I thought it wasn't quite ready for primetime yet, but it seems you're proving that wrong... I'll have to dig in more here, as I'm working embedding WebAssembly in a high performance storage engine.

Thanks for the notes! I hear you on QuickJS - I've seen approaches of folks trying to build more node compatibility on top of quickjs (ala https://github.com/second-state/wasmedge-quickjs), but have recently heard about spidermonkey in wasmtime. Do you have intuition for nodejs vs browser in terms of what people want in terms of compatibility?

"A high-performance, secure, extensible, and OCI-complaint JavaScript runtime for WasmEdge. Run JavaScript in WebAssembly" wasm-edge-quickjs

See potential problems #1 for its proposed changes https://github.com/second-state/wasmedge-quickjs/pull/82#iss...

https://github.com/second-state/wasmedge-quickjs/pull/82#iss...

Try the bot on a PR you're interested in:

I can conceptualize a way to convert JavaScript source code to WASM then convert WASM to C source code. I have considered just using WASM, however, that introduces yet another runtime to manage https://github.com/second-state/wasmedge-quickjs.

Technically you can create a C shared object and import that shared object into QuickJS, see https://github.com/rsenn/qjs-modules, also https://github.com/second-state/wasmedge-quickjs.

That was achieved with QuickJS here https://bellard.org/jslinux/vm.html?url=alpine-x86.cfg, and here https://github.com/second-state/wasmedge-quickjs.

WasmEdge provides excellent support for JavaScript, including ES6 and NPM modules, async networking, the fetch API, React SSR, and even mixing Rust code with JS code. https://github.com/second-state/wasmedge-quickjs

LlamaEdge is not just a lightweight and portable runtime for chatbots. It is an app dev platform for portable LLM apps! RAG chatbots and AI agents can be developed on Mac or Windows, compiled to Wasm, and then deployed across Nvidia / AMD / ARM devices, fully taking advantage of on-device GPUs, NPUs etc.

Hence, besides the LLM runtime, those LLM apps also need to manage embeddings in vector db. This example shows how to access the Qdrant vector db from your portable Wasm apps!

https://github.com/WasmEdge/wasmedge-db-examples/tree/main/q...

The above sample program has been added to the WasmEdge database usage demonstration. You can find the full source code in the GitHub repository at https://github.com/WasmEdge/wasmedge-db-examples/tree/main/greptimedb.

https://github.com/second-state/microservice-rust-mysql

https://github.com/WasmEdge/wasmedge-db-examples

https://github.com/WasmEdge/wasmedge_hyper_demo

WasmEdge is already one of the smallest and most efficient Wasm runtimes out there. It embeds into libsql (SQLite on the server!) to execute user definited functions to perform complex tasks like HTTPS web services & AI inference from SQL statements! https://wasmedge.org/docs/embed/use-case/libsql/

The WasmEdge C++ and Rust SDKs allow host applications to embed Wasm functions asynchronously. It is critically important in many applications where the embedded Wasm function is simply not allowed to block the execution of the host applications. https://github.com/second-state/wasmedge-rustsdk-examples/bl...

Asynchronous host SDKs are complex and a lot of work still remains. We are continuously improving it with our end user and partner communities.

Preview: https://github.com/L-jasmine/WasmEdge/tree/feat/async

What's coming next?

* Support plugins in our Docker and k8s integrations

2.WasmEdge support MySQL-based databases, caches, and DOs. https://github.com/WasmEdge/wasmedge-db-examples