vinum
duckdb
vinum | duckdb | |
---|---|---|
5 | 52 | |
65 | 16,902 | |
- | 5.3% | |
0.0 | 10.0 | |
almost 3 years ago | 2 days ago | |
C++ | C++ | |
BSD 3-clause "New" or "Revised" License | MIT License |
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vinum
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Practical SQL for Data Analysis(what you can do without Pandas)
Following similar observations I was wondering if one can actually execute SQL queries inside of Python process with the access to native Python functions and Numpy as UDFs. Thanks to Apache Arrow one can mix C++ and Python operators without need to copy the data and essentially combine DataFrame API with SQL, all while within the confines of the same Python process.
https://github.com/dmitrykoval/vinum
Vinum allows users to write queries which may invoke any Numpy or Python functions as UDFs available to the interpreter.
- Vinum is a SQL query processor for Python, designed for data analysis workflows
- dmitrykoval/vinum Vinum is a SQL query processor for Python, designed for data analysis workflows and in-memory analytics.
- Vinum – SQL Processor for Python with native Python, Numpy UDF support.
- Show HN: Vinum – SQL Processor for Python with Native Python, Numpy UDF Support
duckdb
- 🪄 DuckDB sql hack : get things SORTED w/ constraint CHECK
- DuckDB: Move to push-based execution model (2021)
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DuckDB performance improvements with the latest release
I'm not sure if the fix is reassuring or not: https://github.com/duckdb/duckdb/pull/9411/files
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Building a Distributed Data Warehouse Without Data Lakes
It's an interesting question!
The problem is that the data is spread everywhere - no choice about that. So with that in mind, how do you query that data? Today, the idea is that you HAVE to put it into a central location. With tools like Bacalhau[1] and DuckDB [2], you no longer have to - a single query can be sharded amongst all your data - EFFECTIVELY giving you a lot of what you want from a data lake.
It's not a replacement, but if you can do a few of these items WITHOUT moving the data, you will be able to see really significant cost and time savings.
[1] https://github.com/bacalhau-project/bacalhau
[2] https://github.com/duckdb/duckdb
- DuckDB 0.9.0
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Push or Pull, is this a question?
[4] Switch to Push-Based Execution Model by Mytherin · Pull Request #2393 · duckdb/duckdb (github.com)
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Show HN: Hydra 1.0 – open-source column-oriented Postgres
it depends on your query obviously.
In general, I did very deep benchmarking of pg, clickhouse and duckdb, and I sure didn't make stupid mistakes like this: https://news.ycombinator.com/item?id=36990831
My dataset has 50B rows and 2tb of data, and I think columnar dbs are very overhiped and I chose pg because:
- pg performance is acceptable, maybe 2-3x times slower than clickhouse and duckdb on some queries if pg is configured correctly and run on compressed storage
- clickhouse and duckdb start falling apart very fast because they specialized on very narrow type of queries: https://github.com/ClickHouse/ClickHouse/issues/47520 https://github.com/ClickHouse/ClickHouse/issues/47521 https://github.com/duckdb/duckdb/discussions/6696
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🦆 Effortless Data Quality w/duckdb on GitHub ♾️
This action installs duckdb with the version provided in input.
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Using SQL inside Python pipelines with Duckdb, Glaredb (and others?)
Duckdb: https://github.com/duckdb/duckdb - seems pretty popular, been keeping an eye on this for close to a year now.
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CSV or Parquet File Format
The Parquet-Go library is very complex, not yet success to use it. So I ask whether DuckDB can provide API https://github.com/duckdb/duckdb/issues/7776
What are some alternatives?
siuba - Python library for using dplyr like syntax with pandas and SQL
ClickHouse - ClickHouse® is a free analytics DBMS for big data
NumCpp - C++ implementation of the Python Numpy library
sqlite-worker - A simple, and persistent, SQLite database for Web and Workers.
turbodbc - Turbodbc is a Python module to access relational databases via the Open Database Connectivity (ODBC) interface. The module complies with the Python Database API Specification 2.0.
datasette - An open source multi-tool for exploring and publishing data
datatable - A Python package for manipulating 2-dimensional tabular data structures
octosql - OctoSQL is a query tool that allows you to join, analyse and transform data from multiple databases and file formats using SQL.
q - q - Run SQL directly on delimited files and multi-file sqlite databases
metabase-clickhouse-driver - ClickHouse database driver for the Metabase business intelligence front-end
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
datafusion - Apache DataFusion SQL Query Engine