GoKawiilAnalysis argues Pandas should be replaced by Polars and DuckDB for mid-size data
A conference talk and blog post argue that Pandas pushes users toward costly distributed systems like Spark or Snowflake long before their data actually requires that complexity. The author says most workloads that hit the 'Pandas cliff' around tens of gigabytes can instead be handled efficiently on a single machine using newer tools such as Polars and DuckDB, up to roughly the 100GB mark. Citing an Amazon Redshift fleet study, the piece suggests genuinely 'Big Data' scale is far rarer than commonly assumed.