Malloy is an alternative to dbt, they have a similar product called Malloyyo [1], and Publisher [3], you can also the chat with HN data demo they have [4].
DBTCharts says you can serve charts locally, but it seems they want you to use their hosting service in production. Whereas, Malloyyo / Publisher are free to use anywhere. If you like college football checkout how I visualize drive data in [2], made with Malloyyo.
Worth separating the layers though, because "alternative to dbt" undersells what Malloy is for. dbt transforms and materializes tables. Malloy describes what the tables mean -- dimensions, measures, join paths, who's allowed to see what -- and compiles that down to SQL. It sits on top of dbt models fine, and plenty of people run it exactly that way.
Publisher runs the model: you define the what, the engine figures out how. You write down what counts as a sale, how revenue is calculated, who sees which rows. Reshaping the data out of the form your systems store it in, deciding what to precompute, serving whichever agent or dashboard or API is asking -- that's the Publisher's job.
A chart spec has to get its numbers from somewhere. If "revenue" is defined inline in the chart's SQL, the definition problem moved, it didn't get solved. Define it once in a model and the chart just renders it.
Same. Almost every time I would use its streaming interfaces in Python, it would STILL materialize everything into memory. That was like 6 months ago. Maybe streaming interfaces actually work, but I found them to be leaky abstractions that required a ton of hand holding to make sure they didn't build a bunch of memory pressure, if you're lucky enough to even have a way to do it.
For example, last time I used it, you couldn't do NDJSON streaming scans from S3 (looks like fixed with PR #26563).
Thanks for sharing, and thanks for making the video you shared. A couple thoughts. Is PostGIS king in this area? I've been liking duckDB as it does not require a server. Is there a good alternative to PostGIS in the duckDB world? Maybe just plain GeoParquet files read in through duckDB?
In the example in your video are any special GEOMETRY functions being used in the underlying SQL? Or, could your data just have been in plain postgres?
A similar product GeoSQL is Malloy which puts a semantic layer on top of your data for better LLM understanding. Malloyyo gives you an MCP server for precise and auditable interaction with your data.
Thanks for the comment! Vercel is a generic cloud provider, so you won’t get any of the MCP specific features (listed in the post) and development experience - monetization is still not regulated by the protocol, so people would pay for your product before using your MCP, then you can charge based on subscription or usage as usual!
If you are a data scientist or do anything with data... duckdb is like a swiss army knife. So many great ways it can help your workflow. The original video from CMU in 2020 [1] is a classic. Minutes 3-8 present a good argument for adding duckdb to your data cleaning/processing workflow.
And if you want to add a semantic layer on top of data, Malloy [2] is my favorite so far (it has duckdb built in):
DBTCharts says you can serve charts locally, but it seems they want you to use their hosting service in production. Whereas, Malloyyo / Publisher are free to use anywhere. If you like college football checkout how I visualize drive data in [2], made with Malloyyo.
[1] - https://github.com/malloydata/malloyyo [2] - https://mrtimo.github.io/cfb-games/games-2026.html?%24SEASON... [3] - https://github.com/malloydata/publisher [4] - https://community.credibledata.com/hackernews
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