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Pandas perform operations on a single machine, whereas PySpark performs operations on multiple machines. This makes it 100x times faster** than Pandas for large datasets. Pandas DataFrames are incapable of constructing a scalable application, but PySparks are ideal for developing scalable applications. As Data is increasing, the need for more frameworks like PySpARK is increasing. For small datasets of 10–12 GB, you can prefer Pandas over the same runtime and with less complexity.