Why Malloy?
Simple naming and practical reusability. Save time by avoiding repetitive definition writing.
Prevents the frustration of seemingly accurate queries leading to incorrect results.
Easier to read, write, and comprehend.
Refine your model iteratively as you query.
How it works
Malloy queries are concise and reader-friendly. They seamlessly translate into SQL, optimized for your database.
Malloy's semantic data modeling allows you to effortlessly craft and recycle intricate business logic.
Daunting, intricate SQL challenges become straightforward in Malloy.
Hands down the cleanest implementation
of a better SQL I've seen so far.
Idris Munk
Nested Queries
Discover how easy it is to write queries using Malloy to produce rich hierarchical views of data.
No more rewriting queries to create hierarchies. Queries are reusable components in Malloy.
See relationships and dimensions of the data simultaneously - giving you unparalleled insights.
Symmetric Aggregates
Malloy automatically prevents miscalculating aggregates such as sums, averages, and counts. This helps take a huge burden off analyst's shoulders who risk charging ahead with incorrect data.
This feels like magic.
Lloyd Tabb
Freedom and Safety
SQL offers maximum freedom, but no safety. - and it’s impossible to save or reuse calculations in a data model.
Existing semantic data models, like LookML, provide safety but restrict analytical freedom.
Malloy combines the safety of a semantic data model with the full flexibility of a relational query language.
How to Get Started
Check out our Quickstart tutorial:
Malloy Quickstart
Learn more on our Documentation page:
Malloy Documentation
Install our VSCode Extension and start writing Malloy on your own datasets:
Visual Studio Marketplace
Join the Slack community – share what you’ve built, ask questions, and give us feedback!
Malloy Slack