db-benchmark
crystal
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db-benchmark | crystal | |
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91 | 239 | |
320 | 19,110 | |
0.9% | 0.5% | |
0.0 | 9.8 | |
10 months ago | 7 days ago | |
R | Crystal | |
Mozilla Public License 2.0 | Apache License 2.0 |
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db-benchmark
- Database-Like Ops Benchmark
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Polars
Real-world performance is complicated since data science covers a lot of use cases.
If you're just reading a small CSV to do analysis on it, then there will be no human-perceptible difference between Polars and Pandas. If you're reading a larger CSV with 100k rows, there still won't be much of a perceptible difference.
Per this (old) benchmark, there are differences once you get into 500MB+ territory: https://h2oai.github.io/db-benchmark/
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DuckDB performance improvements with the latest release
I do think it was important for duckdb to put out a new version of the results as the earlier version of that benchmark [1] went dormant with a very old version of duckdb with very bad performance, especially against polars.
[1] https://h2oai.github.io/db-benchmark/
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Show HN: SimSIMD vs. SciPy: How AVX-512 and SVE make SIMD cleaner and ML faster
https://news.ycombinator.com/item?id=33270638 :
> Apache Ballista and Polars do Apache Arrow and SIMD.
> The Polars homepage links to the "Database-like ops benchmark" of {Polars, data.table, DataFrames.jl, ClickHouse, cuDF, spark, (py)datatable, dplyr, pandas, dask, Arrow, DuckDB, Modin,} but not yet PostgresML? https://h2oai.github.io/db-benchmark/ *
LLM -> Vector database: https://en.wikipedia.org/wiki/Vector_database
/? inurl:awesome site:github.com "vector database"
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Pandas vs. Julia โ cheat sheet and comparison
I agree with your conclusion but want to add that switching from Julia may not make sense either.
According to these benchmarks: https://h2oai.github.io/db-benchmark/, DF.jl is the fastest library for some things, data.table for others, polars for others. Which is fastest depends on the query and whether it takes advantage of the features/properties of each.
For what it's worth, data.table is my favourite to use and I believe it has the nicest ergonomics of the three I spoke about.
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Any faster Python alternatives?
Same. Numba does wonders for me in most scenarios. Yesterday I've discovered pola-rs and looks like I will add it to the stack. It's API is similar to pandas. Have a look at the benchmarks of cuDF, spark, dask, pandas compared to it: Benchmarks
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Pandas 2.0 (with pyarrow) vs Pandas 1.3 - Performance comparison
The syntax has similarities with dplyr in terms of the way you chain operations, and itโs around an order of magnitude faster than pandas and dplyr (thereโs a nice benchmark here). Itโs also more memory-efficient and can handle larger-than-memory datasets via streaming if needed.
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Pandas v2.0 Released
If interested in benchmarks comparing different dataframe implementations, here is one:
https://h2oai.github.io/db-benchmark/
- Database-like ops benchmark
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Python "programmers" when I show them how much faster their naive code runs when translated to C++ (this is a joke, I love python)
Bad examples. Both numpy and pandas are notoriously un-optimized packages, losing handily to pretty much all their competitors (R, Julia, kdb+, vaex, polars). See https://h2oai.github.io/db-benchmark/ for a partial comparison.
crystal
- A Language for Humans and Computers
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Top Paying Programming Technologies 2024
27. Crystal - $77,104
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Crystal 1.11.0 Is Released
I like the first code example on https://crystal-lang.org
# A very basic HTTP server
- Is Fortran "A Dead Language"?
- Choosing Go at American Express
- Odin Programming Language
- I Love Ruby
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Ruby 3.3's YJIT: Faster While Using Less Memory
Obviously as an interpreted language, it's never going to be as fast as something like C, Rust, or Go. Traditionally the ruby maintainers have not designed or optimized for pure speed, but that is changing, and the language is definitely faster these days compared to a decade ago.
If you like the ruby syntax/language but want the speed of a compiled language, it's also worth checking out Crystal[^1]. It's mostly ruby-like in syntax, style, and developer ergonomics.[^2] Although it's an entirely different language. Also a tiny community.
[1]: https://crystal-lang.org/
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What languages are useful for contribution to the GNOME project.
Crystal is a nice language that's not only simple to read and write but performs very well too. And the documentation is amazing as well.
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Jets: The Ruby Serverless Framework
Ruby is a super fun scripting language. I much prefer it to python when I need something with a little more "ooomph" than bash. It's just...nice...to write in. Ruby performance has come a long way in the last decade as well. There's libraries for pretty much everything.
My modern programming toolkit is basically golang + ruby + bash and I am never left wanting.
I do find Crystal (https://crystal-lang.org/) really interesting and am hoping it has its own "ruby on rails" moment that helps the language reach a tipping point in popularity. All the beauty of ruby with all of the speed of Go (and then some, it often compares favorably to languages like rust in benchmarks).
What are some alternatives?
polars - Dataframes powered by a multithreaded, vectorized query engine, written in Rust
zig - General-purpose programming language and toolchain for maintaining robust, optimal, and reusable software.
datafusion - Apache DataFusion SQL Query Engine
Nim - Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).
Apache Arrow - Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing
go - The Go programming language
databend - ๐๐ฎ๐๐ฎ, ๐๐ป๐ฎ๐น๐๐๐ถ๐ฐ๐ & ๐๐. Modern alternative to Snowflake. Cost-effective and simple for massive-scale analytics. https://databend.com
Elixir - Elixir is a dynamic, functional language for building scalable and maintainable applications
DataFramesMeta.jl - Metaprogramming tools for DataFrames
mint-lang - :leaves: A refreshing programming language for the front-end web
sktime - A unified framework for machine learning with time series
Odin - Odin Programming Language