duckdb
sql.js-httpvfs
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duckdb | sql.js-httpvfs | |
---|---|---|
52 | 15 | |
16,576 | 3,233 | |
10.7% | - | |
10.0 | 1.5 | |
2 days ago | about 1 year ago | |
C++ | TypeScript | |
MIT License | Apache License 2.0 |
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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.
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
sql.js-httpvfs
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A future for SQL on the web (2021)
I couldn't find do these wrappers support read-only SQLite databases with HTTP range requests, like in this famous post [1]. Phiresky's wrapper supports it, but it seems to be rebuilding the whole sql.js [2], I'd rather have it as VFS on top of sqlite.org's own WASM module. I like the idea of HTTP range requests, but I don't want to run a fork, that will be unmaintained in few years.
[1]: https://news.ycombinator.com/item?id=27016630
[2]: https://github.com/phiresky/sql.js-httpvfs
- Cloud Backed SQLite
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Transmission 4.0.0 beta 1 is out
Oh that’s an interesting idea. I saw someone built SQLite over HTTP with the Range header: https://phiresky.github.io/blog/2021/hosting-sqlite-database...
So presumably in a similar manner as https://github.com/phiresky/sql.js-httpvfs you could map SQLite pages to leaf torrents too and get the chunking you are looking for.
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netgrep - An experimental porting of ripgrep on WASM over the HTTP protocol.
But ripgrep has to read the whole file; if your intended use case is searching a blog, I'd recommend using something which makes an index, so you don't need to download everything. For example, sql.js-httpvfs is SQLite ported to wasm, with the DB file read over HTTP. If you use FTS to make an index, it works astonishingly well for text search.
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Datasette Lite: a server-side Python web application running in a browser
How close is Python SQLite and Datasette Lite to accessing a hosted SQL database using HTTP range requests as can be done in sql.js like https://github.com/phiresky/sql.js-httpvfs?
I put together a Pyodide-based web app where users need a few indexed queries from a 600mb SQLite database but it isn't very practical for them to download the whole thing into the browser.
https://observablehq.com/@thadk/life
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Ws4sqlite: Query SQLite via HTTP
You can also access sqlite databases directly from an http server that supports range requests (like s3). There are a bunch of implementations of this in different languages including Go[0] and Javascript[1].
[0]: https://github.com/psanford/sqlite3vfshttp
[1]: https://github.com/phiresky/sql.js-httpvfs
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Static torrent website with peer-to-peer queries over BitTorrent on 2M records
Thanks to SQLite VFS abstraction, it is possible to implement your own file system on which SQLite parks data and structures. Inspired by Phiresky's sql.js-httpvfs which uses HTTP Range requests to lazy load blocks of storage from a static web server, I changed few lines of code to point the VFS read() calls to a database seeded by peers as a torrent. A 300 MiB db with 2 million records can be queried from seeders for full text searches in less than 2 MiB traffic with the BitTorrent protocol, all inside the browser, in a static website.
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WebVM: Server-less x86 virtual machines in the browser
Hosting SQLite Databases on GitHub Pages" https://news.ycombinator.com/item?id=28021766 : DuckDB can query [and page] Parquet from GitHub, sql.js-httpvfs, sqltorrent, File System Access API (Chrome only so far; IDK about resource quotas and multi-GB datasets), serverless search with WASM workers
https://github.com/phiresky/sql.js-httpvfs :
> sql.js is a light wrapper around SQLite compiled with EMScripten for use in the browser (client-side).
> This repo is a fork of and wrapper around sql.js to provide a read-only HTTP-Range-request based virtual file system for SQLite. It allows hosting an SQLite database on a static file hoster and querying that database from the browser without fully downloading it.
> The virtual file system is an emscripten filesystem with some "smart" logic to accelerate fetching with virtual read heads that speed up when sequential data is fetched. It could also be useful to other applications, the code is in lazyFile.ts. It might also be useful to implement this lazy fetching as an SQLite VFS [*] since then SQLite could be compiled with e.g. WASI SDK without relying on all the emscripten OS emulation.
- Show HN: Link-Archive.org
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Database-Less Torrent Website
It doesn't have to be range requests, you could split the file instead of depending on the range requests. Essentially it's the same as the chunking instructions for hosters who have a maximum file size as is demonstrated here: https://github.com/phiresky/sql.js-httpvfs/blob/master/creat...
What are some alternatives?
ClickHouse - ClickHouse® is a free analytics DBMS for big data
alasql - AlaSQL.js - JavaScript SQL database for browser and Node.js. Handles both traditional relational tables and nested JSON data (NoSQL). Export, store, and import data from localStorage, IndexedDB, or Excel.
sqlite-worker - A simple, and persistent, SQLite database for Web and Workers.
datasette - An open source multi-tool for exploring and publishing data
sqlite3vfshttp - Go sqlite3 http vfs: query sqlite databases over http with range headers
octosql - OctoSQL is a query tool that allows you to join, analyse and transform data from multiple databases and file formats using SQL.
wp-sqlite-db - A single file drop-in for using a SQLite database with WordPress. Based on the original SQLite Integration plugin.
metabase-clickhouse-driver - ClickHouse database driver for the Metabase business intelligence front-end
sqltorrent
arrow-datafusion - Apache DataFusion SQL Query Engine
webvm - Virtual Machine for the Web