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Ask HN: Tools to visualize data in SQL databases?

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Re: Ask HN: Tools to visualize data in SQL databases?

#12

Maybe not exactly what you are looking for but Datasette is brilliant for SQLite (and csv) https://datasette.io/

It doesn't speak MariaDB (yet - I have a long-term goal to investigate adding alternative database backends as plugins) but you can instead use the https://datasette.io/tools/db-to-sqlite CLI tool to convert a PostgreSQL or MySQL (or other SQL Alchemy supported) database to SQLite, then use Datasette against the resulting file.

This actually works pretty well for small (Then you can visualize with plugins such as https://datasette.io/plugins/datasette-cluster-map or https://datasette.io/plugins/datasette-vega

I also often load data into Datasette and then do custom visualizations in Observable Notebooks by fetching data back out through the Datasette JSON API - here's an example notebook that does that, using the Observable Plot charting library: https://observablehq.com/@simonw/datasette-downloads-per-day...

Re: Ask HN: Tools to visualize data in SQL databases?

#13
post #10

This may be an unpopular opinion, but if you have US$70/mo to spare, it's hard to beat Tableau for this exact use case. "Connect to an arbitrary database, create a view that joins numerous tables (including foreign tables, via blending) together, load to columnar storage on a local SSD for performance if necessary, add arbitrary derived columns (including well-defined lateral lookups for things like 'annotate this ac…

>This may be an unpopular opinion, but if you have US$70/mo to spare, it's hard to beat Tableau for this exact use case.

This is a popular opinion, in my book.

Re: Ask HN: Tools to visualize data in SQL databases?

#14
post #10

This may be an unpopular opinion, but if you have US$70/mo to spare, it's hard to beat Tableau for this exact use case. "Connect to an arbitrary database, create a view that joins numerous tables (including foreign tables, via blending) together, load to columnar storage on a local SSD for performance if necessary, add arbitrary derived columns (including well-defined lateral lookups for things like 'annotate this ac…

As you get deeper into it they hook you into the server and other stuff and it ends up costing 000s.

Pandas is better but requires programming.

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