DuckDB vs MySQL

Query 50GB Parquet files on S3 directly from Python without ETL, returning results in seconds

Replace pandas aggregations with SQL-based DuckDB queries for 10-50x faster group-by operations

Run dbt models locally against DuckDB instead of cloud warehouses to cut development cycle time

Use DuckDB as a compute engine over Delta Lake or Iceberg tables without a dedicated cluster

MySQL replication routes heavy analytical queries to a read replica, removing contention with write-heavy OLTP traffic and keeping application response times below 100ms during peak loads.

MySQL's InnoDB full-text index supports natural language and boolean search queries on text columns without a separate Elasticsearch deployment for basic in-app search needs.

ProxySQL in front of MySQL pools thousands of application connections into tens of database connections, preventing connection exhaustion on deployments that scale web processes horizontally.