Join me for an insightful conversation with Alex Monahan, who works on documentation, tutorials, and training at DuckDB Labs. We explore why DuckDB is gaining momentum among Python and data enthusiasts, from its in-process database design to its blazingly fast, columnar architecture. We also dive into indexing strategies, concurrency considerations, and the fascinating way MotherDuck (the cloud companion to DuckDB) handles large-scale data seamlessly. Don’t miss this chance to learn how a single pip install could totally transform your Python data workflow!

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Links from the show

Alex on Mastodon: @__Alex__

DuckDB: duckdb.org

MotherDuck: motherduck.com

SQLite: sqlite.org

Moka-Py: github.com

PostgreSQL: www.postgresql.org

MySQL: www.mysql.com

Redis: redis.io

Apache Parquet: parquet.apache.org

Apache Arrow: arrow.apache.org

Pandas: pandas.pydata.org

Polars: pola.rs

Pyodide: pyodide.org

DB-API (PEP 249): peps.python.org/pep-0249

Flask: flask.palletsprojects.com

Gunicorn: gunicorn.org

MinIO: min.io

Amazon S3: aws.amazon.com/s3

Azure Blob Storage: azure.microsoft.com/products/storage

Google Cloud Storage: cloud.google.com/storage

DigitalOcean: www.digitalocean.com

Linode: www.linode.com

Hetzner: www.hetzner.com

BigQuery: cloud.google.com/bigquery

DBT (Data Build Tool): docs.getdbt.com

Mode: mode.com

Hex: hex.tech

Python: www.python.org

Node.js: nodejs.org

Rust: www.rust-lang.org

Go: go.dev

.NET: dotnet.microsoft.com

Watch this episode on YouTube: youtube.com

Episode #491 deep-dive: talkpython.fm/491

Episode transcripts: talkpython.fm

Subscribe to Talk Python on YouTube: youtube.com

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Talk Python on Mastodon: talkpython

Michael on Bluesky: @mkennedy.codes at bsky.app

Michael on Mastodon: mkennedy