Goodbye, Node.js Buffer

This page summarizes the projects mentioned and recommended in the original post on news.ycombinator.com

InfluxDB – Built for High-Performance Time Series Workloads
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  1. proposal-zero-copy-arraybuffer-list

    A proposal for zero-copy ArrayBuffer lists

  2. InfluxDB

    InfluxDB – Built for High-Performance Time Series Workloads. InfluxDB 3 OSS is now GA. Transform, enrich, and act on time series data directly in the database. Automate critical tasks and eliminate the need to move data externally. Download now.

    InfluxDB logo
  3. WebGL-Fluid-Simulation

    Play with fluids in your browser (works even on mobile)

    Typed arrays are essential for web apps that use WebGL and WebGPU. Being able to send this typed data to run computations on the GPU in parallel can give you 1000x speed up.

    You can see it in action on this WebGL fluid simulator[0] by PavelDoGreat.

    [0] https://github.com/PavelDoGreat/WebGL-Fluid-Simulation

  4. uint8array-extras

    Useful utilities for working with Uint8Array (and Buffer)

    I wonder why you would introduce an extra dependency for the base64 example. It seems more trivial than left pad.

    https://github.com/sindresorhus/uint8array-extras/blob/cbf24...

  5. falcon

    Brushing and linking for big data (by vega)

  6. nodejs-polars

    nodejs front-end of polars

  7. arquero

    Query processing and transformation of array-backed data tables.

    https://github.com/uwdata/arquero

  8. SaaSHub

    SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

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  9. parquet-wasm

    Rust-based WebAssembly bindings to read and write Apache Parquet data

    nodejs-polars is node-specific and uses native FFI. polars can be compiled to Wasm but doesn't yet have a js API out of the box.

    As for the fastest way to serialize data to Pandas data to the browser, you should use Parquet; it's the fastest to write on the Python side and read on the JS side, while also being compressed. See https://github.com/kylebarron/parquet-wasm (full disclosure, I wrote this)

  10. proposal-arraybuffer-base64

    TC39 proposal for Uint8Array<->base64/hex

    The proposal for native base64 support for Uint8Arrays is mine. I'm glad to see people are interested in using it. (So am I!)

    For a status update, for the last year or two the main blocker has been a conflict between a desire to have streaming support and a desire to keep the API small and simple. That's now resolved [1] by dropping streaming support, assuming I can demonstrate a reasonably efficient streaming implementation on top of the one-shot implementation, which won't be hard unless "reasonably efficient" means "with zero copies", in which case we'll need to keep arguing about it.

    I've also been working on documenting [2] the differences between various base64 implementations in other languages and in JS libraries to ensure we have a decent picture of the landscape when designing this.

    With luck, I hope to advance the proposal to stage 3 ("ready for implementations") within the next two meetings of TC39 - so either next month or January. Realistically it will probably take a little longer than that, and of course implementations take a while. But it's moving along.

    [1] https://github.com/tc39/proposal-arraybuffer-base64/issues/1...

    [2] https://gist.github.com/bakkot/16cae276209da91b652c2cb3f612a...

  11. proposal-resizablearraybuffer

    Discontinued Proposal for resizable array buffers

    Nit: "fixed-length" is no longer true as of very recently [1].

    [1] https://github.com/tc39/proposal-resizablearraybuffer

  12. proposal-array-from-async

    Draft specification for a proposed Array.fromAsync method in JavaScript.

  13. proposal-async-iterator-helpers

    Methods for working with async iterators in ECMAScript

  14. streams

    Streams Standard

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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