Even if your dataset is under 500 MB, handling 26 million rows can be quite intensive. So first question to ask, do you really need all that data ? Why don't you aggregate it ?
So, you can also reduce the number of columns, filtering out unnecessary rows, and using data aggregations or summaries where possible. Verify also the data types as inappropriate data types can consume more memory.
2 things in my mind : split your data into smaller chunks or use incremental refresh.
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