DuckDB is an in-memory analytical database system that aims to provide high performance and efficient querying for analytical workloads. It is designed to handle large datasets and perform complex analytical queries with low latency. DuckDB's architecture focuses on columnar storage and vectorized query execution, making it well-suited for data analysis tasks. It supports SQL queries and can be integrated into various programming languages and frameworks.

What’s better about this method or library

Often analytical workloads are relatively small, even for companies that host large data warehouses. This is because the scope for reports and analytics usually span within a limited time frame, such as within a month, a quarter, or a year. Given the amount of data, we can avoid the hassle of permission handling and waiting for developer operations and instead create a report environment more localized to our analytics team.

What can we do with it

Along with practices to archive our data (to CSV or Parquet), we can use this as our first few steps into data analytics and engineering.

How should we adopt it

We can adopt it gradually, through aggregating our internal data, or through creating embedded interfaces with DuckDB WASM to replace and simplify our data warehousing needs.

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