ibis
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ibis | sqlite_scanner | |
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22 | 4 | |
3,928 | 184 | |
13.2% | 3.3% | |
10.0 | 8.3 | |
5 days ago | about 1 month ago | |
Python | C | |
Apache License 2.0 | MIT License |
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ibis
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This Week In Python
ibis – portable Python dataframe library
- FLaNK Stack 26 February 2024
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Quarto
The main benefit is that you get a Python (or R, Julia or Rust) interpreter. So you can evaluate code. A good example of the value of this is the Ibis docs which use Quarto: https://ibis-project.org/
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Polars – A bird's eye view of Polars
Ive found polars quite intuitive, though for python, I lean more towards [ibis](https://ibis-project.org/). The interface is nearly identical, but ibis has the benefit if building sql queries before pulling any actual data (like dbplyr) — whereas polars requires the data to be in-memory (at least for rdb’s, though correct me if Im wrong)
this to me seems like a good argument for only using ibis, but Im happy to be convinced otherwise
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Vanna.ai: Chat with your SQL database
Please add Ibis Birdbrain https://ibis-project.github.io/ibis-birdbrain/ to the list. Birdbrain is an AI-powered data bot, built on Ibis and Marvin, supporting more than 18 database backends.
See https://github.com/ibis-project/ibis and https://ibis-project.org for more details.
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How to Use Pandas for Data Analysis
Ibis: The portable Python dataframe library
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Upcoming Data Engineering Tools
We have Ibis which helps you write generic analytics pipelines and it supports multiple backends and you can either run these pipeline on a query processing engine or a pyspark cluster or even on Pandas or Polars.
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A LLM+OLAP Solution
Ibis could also be a target. It compiles queries written in python to multiple dataframe libraries, and SQL targets.
- DuckDB: Querying JSON files as if they were tables
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DuckDB – in-process SQL OLAP database management system
You might be interested in checking out Ibis (https://ibis-project.org/). It provides a dataframe-like API, abstracting over many common execution engines (duckdb, postgres, bigquery, spark, ...). Ibis wrapping duckdb has pretty much replaced pandas as my tool of choice for local data analysis. All the performance of duckdb with all the ergonomics of a dataframe API. (disclaimer: I contribute to Ibis for work).
sqlite_scanner
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DuckDB 0.7.0
It's not a dumb question at all. I'm pretty knowledgeable with DBs and still find it very difficult to understand how many of these front-end/pass-through engines work.
Checkout Postgres Foreign Data Wrappers. That might be the most well known approach for accessing one database through another. The Supabase team wrote an interesting piece about this recently.
https://supabase.com/blog/postgres-foreign-data-wrappers-rus...
You might also want to try out duckdb's approach to reading other DBs (or DB files). They talk about how they can "import" a sqlite DB in the above 0.7.0 announcement, but also have some other examples in their duckdblabs github project. Check out their "...-scanner" repos:
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Notes on the SQLite DuckDB Paper
DuckDB can actually read SQLite or Postgres directly! In the SQLite case, something like Litestream plus DuckDB could work really well!
Also, with Pyarrow's help, DuckDB can already do this with Delta tables!
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Friendlier SQL with DuckDB
Excellent question! I'll jump in - I am a part of the DuckDB team though, so if other users have thoughts it would be great to get other perspectives as well.
First things first - we really like quite a lot about the SQLite approach. DuckDB is similarly easy to install and is built without dependencies, just like SQLite. It also runs in the same process as your application just like SQLite does. SQLite is excellent as a transactional database - lots of very specific inserts, updates, and deletes (called OLTP workloads). DuckDB can also read directly out of SQLite files as well, so you can mix and match them! (https://github.com/duckdblabs/sqlitescanner)
DuckDB is much faster than SQLite when doing analytical queries (OLAP) like when calculating summaries or trends over time, or joining large tables together. It can use all of your CPU cores for sometimes ~100x speedup over SQLite.
DuckDB also has some enhancements with respect to data transfer in and out of it. It can natively read Pandas, R, and Julia dataframes, and can read parquet files directly also (meaning without inserting first!).
Does that help? Happy to add more details!
What are some alternatives?
snowflake-connector-python - Snowflake Connector for Python
PySpark-Boilerplate - A boilerplate for writing PySpark Jobs
Apache Impala - Apache Impala
pangres - SQL upsert using pandas DataFrames for PostgreSQL, SQlite and MySQL with extra features
react-native-quick-sqlite - Fast SQLite for react-native.
nodejs-polars - nodejs front-end of polars
katacoda
django-clickhouse - This project's goal is to build Yandex ClickHouse database into Django project.
ClickBench - ClickBench: a Benchmark For Analytical Databases
store - PostgreSQL shopping cart
prql - PRQL is a modern language for transforming data — a simple, powerful, pipelined SQL replacement
xonsh - :shell: Python-powered, cross-platform, Unix-gazing shell.