- Jan 20, 2026
- 3 min read
Why should you care about DuckDB?
People call DuckDB the “opposite of Redshift” not because they do different things, but because of where and how they do them.
While both are OLAP (analytical) databases that use columnar storage, they sit at two extreme ends of the infrastructure spectrum. The most common shorthand is: “DuckDB is to Redshift what SQLite is to PostgreSQL.”
Here is why they are considered opposites:
1. The Location: Local vs. Remote
- Redshift is a Centralized Cloud Warehouse. To use it, you have to send your data over the internet to a massive cluster of servers managed by AWS. There is “network latency” every time you ask a question.
- DuckDB is an In-Process (Embedded) Database. It lives inside your application (like your Python script or your BI tool). There is zero network latency because the database is literally running in the same memory as your code.
2. The Scale: Distributed vs. Single-Node
- Redshift is Distributed. It uses “Massively Parallel Processing” (MPP), meaning it splits one query across dozens or hundreds of different computers to handle petabytes of data.
- DuckDB is Single-Node. It is hyper-optimized to squeeze every ounce of power out of a single machine (like your laptop). It can’t “cluster” multiple computers together, but it can process millions of rows on your MacBook faster than Redshift can even establish a connection.
3. The Management: Heavyweight vs. Zero-Config
- Redshift is a beast to manage. Even “Serverless” Redshift involves setting up IAM roles, VPCs, security groups, and handling data ingestion (ETL).
- DuckDB has no installation. You just
pip install duckdb. There are no users to manage, no servers to restart, and no config files. It’s a single file that “just works.”
Comparison Summary: “Big Data” vs. “Small Data”
The “opposite” labels often stem from the “Big Data is Dead” movement.
| Feature | Amazon Redshift | DuckDB |
|---|---|---|
| Philosophy | ”Bring the data to the warehouse." | "Bring the warehouse to the data.” |
| Hardware | A cluster of 100s of servers. | Your laptop’s CPU and RAM. |
| Setup Time | Hours to Days. | 2 seconds. |
| Data Gravity | You move data into Redshift. | It queries Parquet/CSV files where they sit. |
| Cost | Thousands of dollars per month. | Free / Cost of your own hardware. |
When to use which?
- Use Redshift if you are an enterprise with 100+ TBs of data and hundreds of people running reports at the same time.
- Use DuckDB if you are a data scientist or developer working with under 1 TB of data and you want to run SQL queries instantly on your own machine without paying AWS a dime.
Would you like to see a quick example of how DuckDB can query a file sitting on your computer right now?