apsw
duckdb
| apsw | duckdb | |
|---|---|---|
| 3 | 52 | |
| 696 | 16,749 | |
| - | 4.5% | |
| 9.6 | 10.0 | |
| 2 days ago | 4 days ago | |
| Python | C++ | |
| GNU General Public License v3.0 or later | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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.
apsw
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SQLite version of SQL Server "linkedin server", or another way to query another db from within SQLite?
You can do this with virtual tables, but you'd have to implement the code for the vtab yourself. If you know Python, the APSW SQLite driver supports vtabs. The default one that comes with most Python distros does not
- Hosting SQLite databases on GitHub Pages (or any static file hoster)
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What's New in SQLite 3.35
There is also this, which seems pretty good: https://github.com/rogerbinns/apsw
(haven't tried it yet)
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?
SuperSQLite - A supercharged SQLite library for Python
ClickHouse - ClickHouse® is a free analytics DBMS for big data
dataset - Easy-to-use data handling for SQL data stores with support for implicit table creation, bulk loading, and transactions.
sqlite-worker - A simple, and persistent, SQLite database for Web and Workers.
pymssql - Official home for the pymssql source code.
datasette - An open source multi-tool for exploring and publishing data
asyncpg - A fast PostgreSQL Database Client Library for Python/asyncio.
octosql - OctoSQL is a query tool that allows you to join, analyse and transform data from multiple databases and file formats using SQL.
awesome-mysql - A curated list of awesome MySQL software, libraries, tools and resources
metabase-clickhouse-driver - ClickHouse database driver for the Metabase business intelligence front-end
clickhouse-driver - ClickHouse Python Driver with native interface support
datafusion - Apache DataFusion SQL Query Engine