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Update mention of DuckDB in README #7101

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8 changes: 4 additions & 4 deletions README.Rmd
Original file line number Diff line number Diff line change
Expand Up @@ -49,10 +49,10 @@ In addition to data frames/tibbles, dplyr makes working with other computational
- [dbplyr](https://dbplyr.tidyverse.org/) for data stored in a relational
database. Translates your dplyr code to SQL.

- [duckplyr](https://duckdblabs.github.io/duckplyr/) for using [duckdb](https://duckdb.org) on large, in-memory datasets with zero extra copies. Translates your dplyr code to high performance duckdb queries with an automatic R fallback when translation isn't possible.

- [duckdb](https://duckdb.org/docs/api/r) for large datasets that are
still small enough to fit on your computer.
- [duckplyr](https://duckplyr.tidyverse.org/) for large, in-memory
datasets. Translates your dplyr code to high performance
[duckdb](https://duckdb.org) queries with zero extra copies and
an automatic R fallback when translation isn’t possible.

- [sparklyr](https://spark.rstudio.com) for very large datasets stored in
[Apache Spark](https://spark.apache.org).
Expand Down
11 changes: 4 additions & 7 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -51,13 +51,10 @@ alternative backends:
- [dbplyr](https://dbplyr.tidyverse.org/) for data stored in a
relational database. Translates your dplyr code to SQL.

- [duckplyr](https://duckdblabs.github.io/duckplyr/) for using
[duckdb](https://duckdb.org) on large, in-memory datasets with zero
extra copies. Translates your dplyr code to high performance duckdb
queries with an automatic R fallback when translation isn’t possible.

- [duckdb](https://duckdb.org/docs/api/r) for large datasets that are
still small enough to fit on your computer.
- [duckplyr](https://duckplyr.tidyverse.org/) for large, in-memory
datasets. Translates your dplyr code to high performance
[duckdb](https://duckdb.org) queries with zero extra copies and
an automatic R fallback when translation isn’t possible.

- [sparklyr](https://spark.rstudio.com) for very large datasets stored
in [Apache Spark](https://spark.apache.org).
Expand Down
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