postgres_scanner VS duckdf

I've created an ODBC DuckDB extension to query any database that has an ODBC driver. It's modeled after the fantastic official Postgres scanner extension https://github.com/duckdblabs/postgres_scanner.

It supports fetching rowsets in batches to minimize network overhead and defaults to the default DuckDB vector size of 2048.

I've tested it against the IBM DB2 & Postgres ODBC drivers and will continue to test and add support for all major databases. If you've got one you'd like to see let me know in the comments.

I've got plenty of improvements in the pipeline including:

It's not a dumb question at all. I'm pretty knowledgeable with DBs and still find it very difficult to understand how many of these front-end/pass-through engines work.

Checkout Postgres Foreign Data Wrappers. That might be the most well known approach for accessing one database through another. The Supabase team wrote an interesting piece about this recently.

https://supabase.com/blog/postgres-foreign-data-wrappers-rus...

You might also want to try out duckdb's approach to reading other DBs (or DB files). They talk about how they can "import" a sqlite DB in the above 0.7.0 announcement, but also have some other examples in their duckdblabs github project. Check out their "...-scanner" repos:

https://github.com/duckdblabs/postgres_scanner

https://github.com/duckdblabs/sqlite_scanner

Doesn't postgres have a columnar option? If so, you could prob get better performance for your analytical interactions if you switched some tables to columnar.

Otherwise check out postgres scanner. https://github.com/duckdblabs/postgres_scanner

DuckDB can actually read SQLite or Postgres directly! In the SQLite case, something like Litestream plus DuckDB could work really well!

Also, with Pyarrow's help, DuckDB can already do this with Delta tables!

https://github.com/duckdblabs/sqlite_scanner

https://github.com/duckdblabs/postgresscanner

Interesting thought! I have not tried this yet so I only have a guess as an answer. Could you export the data as SQL statements and then run those statements on DuckDB? That may be easier to set up, but may take longer to run...

DuckDB also has the ability to read Postgres data directly, and there is a Postgres FDW that can read from DuckDB!

https://github.com/duckdblabs/postgresscanner

https://github.com/alitrack/duckdb_fdw

Quite a while ago, when duckdb was just a duckling, I wrote an R package that supported direct manipulation of R dataframes using SQL.[1] duckdb was the engine for this.

The approach was never as fast as data.table but did approach the speed of dplyr for more complex queries.

Life had other things in store for me and I haven’t touched this library for a while now.

At the time there was no Julia connector for duckdb, but now that there is, I’d like to try this approach in that language.

[1] https://github.com/phillc73/duckdf

Yeah, I agree sqldf is quite slow. Fair point.

As you've seen, duckdb registers an "R data frame as a virtual table." I'm not sure what they mean by "yet" either.

Of course it is possible to write an R dataframe to an on-disk duckdb table, if that's what you want to do.

There are some simple benchmarks on the bottom of the duckdf README[1]. Essentially I found for basic SQL SELECT queries, dplyr is quicker, but for much more complex queries, the duckdf/duckdb combination performs better.

If you really want speed of course, just use data.table.

[1] https://github.com/phillc73/duckdf

That's a really good point that I'd not really thought about. I'd never really considered the difference between calling just functions versus macros.

Thinking about Query.jl and DataFramesMeta.jl, and I am for sure not an expert in either, I can't specifically speak to your `head` example, but other base functions can be combined with macros. For example, see the LINQ examples from DataFramesMeta.jl[1] where `mean` is being used. Or again the LINQ style examples in Query.jl[2], where `descending` is used in the first example, or `length` later in the Grouping examples.

Is that the kind of thing you meant?

For whatever reason, with the way my brain is wired, the LINQ style of query just works for me. I have never directly used LINQ, but do have some SQL experience. In fact, I wrote some dinky little wrapper functions[3] around duckdb[4] so I could directly query R dataframes and datatables with SQL using that backend, rather than sqldf[5].

[1] https://juliadata.github.io/DataFramesMeta.jl/stable/#@linq-...

[2] https://www.queryverse.org/Query.jl/stable/linqquerycommands...

[3] https://github.com/phillc73/duckdf

[4] https://duckdb.org/

[5] https://cran.r-project.org/web/packages/sqldf/index.html