We're open soon for early adopters, but you can see it in action or read the preview docs ⇢
Integrating your spreadsheets with external data and code has huge benefits, enabling models to react instantly— resulting in quicker responses to market and business changes. Hitting a refresh button or loading in some CSV with VBA? Not anymore.
A robust and scalable implementation is harder to pull off than it looks. It often requires development teams to work with unfamiliar, dated trusty (but rusty) technologies.
rtd.pub isolates developers from all of this, allowing them to focus on delivering results. rtd.pub uses a simple plugin model, allowing developers to write plugins that can interface with anything.
With idiomatic SDKs for Go and Python (and support for any language with gRPC libraries), developers can use the environments and ecosystems that they already use. Official plugins for common use cases are open source and free to use and adapt. We even write bespoke plugins for your organization.
Thinking beyond the obvious market and FX price tickers use case— code in any language can react to on-sheet changes and compute results that get returned back to the sheet for display and possibly further computation. Got some legacy pricing logic in C++? An AI model in Python that needs GPUs? Want to prompt an LLM like ChatGPT or Gemini? No bother. Wrap it up as an rtd.pub plugin, with just a few lines of code.
Configuration, basic go plugin and NATS ... in one minute
Shows configuration of the counter plugin from the tutorial, and also the NATS plugin. If you can land your data into NATS subjects, you can stream it into Excel with only configuration. Plugins for other messaging technologies are on the way.
Lightweight and fast
The performance plugin benchmarks some aspects of rtd.pub performance by updating a random selection of topics every 100ms. This sheet has 10000 topics: far more are feasible. CPU load remains low, and Excel responsiveness is good, even on very basic hardware. At the same time, other plugins can be used independently as they run as isolated processes, with output multiplexed and fed into Excel through a single connection. 🤓
Integrates easily with websocket APIs
It is straightforward to connect to external data vendors, including ones that you might already use— this integration uses the polygon.io stocks websocket API (no affiliation) and their official go client.
Register interest with GitHub