db-benchmark
datafusion-ballista
| db-benchmark | datafusion-ballista | |
|---|---|---|
| 12 | 13 | |
| 127 | 1,359 | |
| 3.1% | 6.2% | |
| 6.9 | 8.0 | |
| 4 days ago | 29 days ago | |
| R | Rust | |
| Mozilla Public License 2.0 | Apache License 2.0 |
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db-benchmark
- Database-Like Ops Benchmark
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Polars
DuckDB maintains a benchmark of open source database-like tools, including Polars and Pandas
https://duckdblabs.github.io/db-benchmark/
- Planning a New Benchmarking for Comparing Filter2Groupby for 3,000 Files (100,000 Rows/Files)
- Pandas vs. Julia – cheat sheet and comparison
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Polars supports SQL statement in Python Plus CLI Verion (Polars.exe 24.4MB)
DuckDB is also a SQL/Python app, refer to this benchmark, seem it run very fast https://duckdblabs.github.io/db-benchmark/
- The Return of the H2o.ai Database-Like Ops Benchmark
- I discovered that the fastest way to create a Pandas DataFrame from a CSV file is to actually use Polars
datafusion-ballista
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DataFusion Comet: Apache Spark Accelerator
But why. Just ditch Spark and use https://github.com/apache/datafusion-ballista directly.
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Polars
Not super on topic because this is all immature and not integrated with one another yet, but there is a scaled-out rust data-frames-on-arrow implementation called ballista that could maybe? form the backend of a polars scale out approach: https://github.com/apache/arrow-ballista
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Rust vs. Go in 2023
> Is Rust's compile-time GC about something other than performance somehow?
AFAIK, memory safety and language features as RAII is also available in C++, for instance. About the reasons for slow compilation, take a look at https://www.reddit.com/r/rust/comments/xna9mb/why_are_rust_p...
Not having a GC is also about not having a runtime as you mention (e.g. nice for creating Python extensions and embedded systems programming) and also more runtime deterministic performance: on that, if I'm not mistaken that was the reason for Discourse switching to Rust and also, e.g.: "the choice of Rust as the main execution language avoids the overhead of GC pauses and results in deterministic processing times" https://github.com/apache/arrow-ballista/blob/main/README.md
- Ballista (Rust) vs Apache Spark. A Tale of Woe.
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Evolution and Trends of Data Engineering 2022/23
Ballista (Arrow-Rust), which is largely inspired by Apache Spark, there are some interesting differences.
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Data Engineering with Rust
https://github.com/jorgecarleitao/arrow2 https://github.com/apache/arrow-datafusion https://github.com/apache/arrow-ballista https://github.com/pola-rs/polars https://github.com/duckdb/duckdb
- Any job processing framework like Spark but in Rust?
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Is Apache Arrow DataFusion and Ballista the future of big data engineering/science?
Source: https://github.com/apache/arrow-ballista
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Pure Python Distributed SQL Engine
Can you explain how this might differ from something like https://github.com/apache/arrow-ballista
I've seen several variants of "next-gen" spark, but nowhere have I really seen the different tradeoffs/advantages/disadvantages between them.
- Scala or Rust? which one will rule in future?
What are some alternatives?
Tidier.jl - Meta-package for data analysis in Julia, modeled after the R tidyverse.
duckdb - DuckDB is an analytical in-process SQL database management system
DataFramesMeta.jl - Metaprogramming tools for DataFrames
lance - Modern columnar data format for ML and LLMs implemented in Rust. Convert from parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, DuckDB, Polars, Pyarrow, with more integrations coming..
db-benchmark - reproducible benchmark of database-like ops
seafowl - Analytical database for data-driven Web applications 🪶
connector-x - Fastest library to load data from DB to DataFrames in Rust and Python
datafusion - Apache DataFusion SQL Query Engine
opteryx - 🦖 A SQL-on-everything Query Engine you can execute over multiple databases and file formats. Query your data, where it lives.
sqlglot - Python SQL Parser and Transpiler
comprehensive-rust - This is the Rust course used by the Android team at Google. It provides you the material to quickly teach Rust.
datafusion-python - Apache DataFusion Python Bindings