# \[ANN\] SQLCollections.jl – use Julia data manipulation functions for databases

**URL:** <https://discourse.julialang.org/t/ann-sqlcollections-jl-use-julia-data-manipulation-functions-for-databases/119244>\
**Category:** Package Announcements\
**Tags:** query, database\
**Created:** [September 10, 2024, 9:57am UTC](https://discourse.julialang.org/t/ann-sqlcollections-jl-use-julia-data-manipulation-functions-for-databases/119244 "2024-09-10T09:57:36Z")\
**Posts on this page:** 1\
**Showing post:** 27

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**Author:** ![aplavin](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/aplavin/32/222056_2.png) [@aplavin](https://discourse.julialang.org/u/aplavin)\
**Post date:** [September 26, 2024, 2:18pm UTC](https://discourse.julialang.org/t/ann-sqlcollections-jl-use-julia-data-manipulation-functions-for-databases/119244/27 "2024-09-26T14:18:51Z")

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SQLCollections.jl is finally released in General 🙂

A nice synergy – that basically comes for free – is querying tabular files like CSV or parquet. See the QuackIO.jl package: it could already use DuckDB to performantly read such files into Julia, like `read_csv(StructArray, "my_file.csv")`.  
Now, with SQLCollections.jl, we can query these files without fully loading into memory, while still using the same Julia syntax:

```julia
using QuackIO, SQLCollections

data = read_csv(SQLCollection, "my_file.csv")
# data is an SQLCollection and can easily be queried :)

```

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_[View the full topic](https://discourse.julialang.org/t/ann-sqlcollections-jl-use-julia-data-manipulation-functions-for-databases/119244)._