MotherDuck

DuckDB and MotherDuck simplify geospatial analysis by supporting various spatial formats and offering easy integration with Python libraries for visualization. The post guides you through building a heatmap of EV charging spots in France using DuckDB with a Python visualization tool called Lonboard. It also discusses leveraging cloud computing with MotherDuck for sharing and exporting geospatial data.

Getting started with modern GIS using DuckDB

Simple Thread

Greg Kontos reduced data storage costs by over 99% by migrating his hobby recipe tracking site from a GCP Cloud SQL instance to using DuckDB. Initially faced with a $68/month cost, with $67 of that for the SQL database, Greg explored various alternatives including serverless databases, dataframes, and local databases. He ultimately chose DuckDB for its SQL-like interface, simplicity, and low cost. Despite some minor issues, the transition was successful, lowering monthly costs to just $0.25 and maintaining functionality.

Migrating a small web application from SQL using DuckDB

DuckDB is an open-source, embeddable SQL database engine designed for analytical and data science workloads in Python, R, and other programming languages. It provides features such as columnar storage, vectorized query execution, and multi-threaded processing for efficient query performance and scalability. Readers can explore DuckDB's features, integrations, and use cases for interactive data analysis, data visualization, and machine learning applications, leveraging its lightweight and fast SQL engine for handling large datasets in memory-constrained environments.

Best of DuckDB — September 2024