db-benchmark
datasette
db-benchmark | datasette | |
---|---|---|
91 | 187 | |
320 | 8,955 | |
0.0% | - | |
0.0 | 9.3 | |
10 months ago | 7 days ago | |
R | Python | |
Mozilla Public License 2.0 | Apache License 2.0 |
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Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
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 – 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 it’s around an order of magnitude faster than pandas and dplyr (there’s a nice benchmark here). It’s 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.
datasette
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Ask HN: High quality Python scripts or small libraries to learn from
Simon Willison's github would be a great place to get started imo -
https://github.com/simonw/datasette
- Show HN: TextQuery – Query and Visualize Your CSV Data in Minutes
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Little Data: How do we query personal data? (2013)
I'm a fan on simonw's datasette/dogsheep ecosystem https://datasette.io/
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LaTeX and Neovim for technical note-taking
I use Anki the exact same way. After a lifetime of learning I have accepted that I will never read over anything I write for myself voluntarily - so my two options are:
1. Write an article so good I can publish it and look it over myself later on. I did this last year with https://andrew-quinn.me/fzf/, for example.
2. Create Anki cards out of the material. Use the builtin Card Browser or even https://datasette.io/ on the underlying SQLite database in a pinch to search for my notes any time I have to.
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Daily Price Tracking for Trader Joes
Were you aware of, or tempted by https://datasette.io/ for creating your solution?
- SQLite-Web: Web-based SQLite database browser written in Python
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Ask HN: What two software products should have a kid?
Browsing HN, GitHub and the like we get to see a huge variety of software products and code bases.
I often see products and think - if this product X, got together with Y, it would be pretty cool - kind of like if they had a kid together.
Not too literally, but more on the conceptual level - my level of programming is low.
E.g. Just some....
- pocketable.io & datasette (+with some more charting) [https://pocketbase.io, https://datasette.io]
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Ask HN: Looking for a project to volunteer on? (February 2024)
You might like the Datasette project: https://datasette.io/
I don't think they are desperate for contributions but it's a welcoming environment and a fun project to hack on. You'll learn a lot just from reading the source and the incredibly informative PRs. The creator is a really talented developer with a great blog which shows up on the HN front page often.
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Stuff I Learned during Hanukkah of Data 2023
Last year I worked through the challenges using VisiData, Datasette, and Pandas. I walked through my thought process and solutions in a series of posts.
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What We Watched: A Netflix Engagement Report – About Netflix
> uploads of boring raw excel data and receive a nice UI
https://datasette.io/
What are some alternatives?
polars - Dataframes powered by a multithreaded, vectorized query engine, written in Rust
nocodb - 🔥 🔥 🔥 Open Source Airtable Alternative
datafusion - Apache DataFusion SQL Query Engine
duckdb - DuckDB is an in-process SQL OLAP Database Management System
Apache Arrow - Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing
sql.js-httpvfs - Hosting read-only SQLite databases on static file hosters like Github Pages
databend - 𝗗𝗮𝘁𝗮, 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 & 𝗔𝗜. Modern alternative to Snowflake. Cost-effective and simple for massive-scale analytics. https://databend.com
litestream - Streaming replication for SQLite.
sktime - A unified framework for machine learning with time series
Sequel-Ace - MySQL/MariaDB database management for macOS
DataFramesMeta.jl - Metaprogramming tools for DataFrames
beekeeper-studio - Modern and easy to use SQL client for MySQL, Postgres, SQLite, SQL Server, and more. Linux, MacOS, and Windows.