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update docs to reflect recent changes (joins and window functions) #489

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Jun 23, 2021
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update docs to reflect recent changes (joins and window functions) #489

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5 changes: 1 addition & 4 deletions README.md
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Expand Up @@ -37,10 +37,7 @@ Independently, they support a vast array of functionality for in-memory computat

Together, they allow users to write an SQL query or a `DataFrame` (using the `datafusion` crate), run it against a parquet file (using the `parquet` crate), evaluate it in-memory using Arrow's columnar format (using the `arrow` crate), and send to another process (using the `arrow-flight` crate).

Generally speaking, the `arrow` crate offers functionality to develop code that uses Arrow arrays, and `datafusion` offers most operations typically found in SQL, with the notable exceptions of:

- `join`
- `window` functions
Generally speaking, the `arrow` crate offers functionality to develop code that uses Arrow arrays, and `datafusion` offers most operations typically found in SQL, including `join`s and window functions.

There are too many features to enumerate here, but some notable mentions:

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