Terality vs Spark
Terality makes Pandas as scalable as Apache Spark just by changing the import, and without thinking about servers or clusters. Terality handles all the infrastructure and scaling behind the scenes.
| Spark | Terality |
Dataset's size | Small to Large | Small to Large |
Parallelization on multiple cores for lightning speed | Yes | Yes |
Infrastructure | Custom | Serverless |
Syntax | Scala or PySpark or SparkSQL | Pandas |
Data scientist's autonomy | No | Yes |
Support | None | Yes |
| EMR/Dataproc/Databricks | Terality |
Dataset's size | Small to Large | Small to Large |
Parallelization on multiple cores for lightning speed | Yes | Yes |
Infrastructure | Semi-managed | Serverless |
Syntax | Scala or PySpark or SparkSQL | Pandas |
Data scientist's autonomy | No | Yes |
Support | Yes | Yes |
Last modified 1yr ago