Brim Data Blog
At Brim we're building a way to work with data that is flexible yet fully-structured, able to explore messy JSON or typed relational tables.
Stay up to date on Brim, the Zed project, and super-structured data.
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Versions have been synchronized, inspect data in the detail pane, and perform multi-pool search much faster.
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Read about red squiggly lines, Apple silicon, Pretty JSON, and more.
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You've got CSV data. You want to run sophisticated queries against it. Does that mean you need to turn it into SQL tables first?
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The Zed data source for Grafana is now available for visualizing the data in your Zed lake.
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We’ve all experienced the pain of debugging our data when something changes upstream. Zed makes finding and fixing data problems much easier with its first-class error data type.
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Comparing a jq program with the equivalent zq script and noticing how much further you go can with the data due to Zed's rich data types.
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As yet another way to learn and use Zed, 'zq' can now run right in your browser with the zed-wasm npm package.
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The Zed data model was designed to harness the power of both relational tables and schema-less objects. Let's see how it handles arrays.
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As an alternative to crude text searches with grep and the like, I use Zed and Zui to explore a large, messy JSON object.
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We needed a name that clearly tied the app to Zed. After many fun naming sessions, we played off the word "GUI" and landed on "Zui": The Zed user interface.
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Have you ever gotten frustrated deserializing JSON into a Go interface value? Turns out you're not the only one!
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Dealing with real-world data is hard. You often end up stuck between the document model of JSON and the relational model of SQL databases. There's a better way. It's called super-structured data.
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Take an in-depth look at the different computational models of zq and jq.
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