AWS Glue DataBrew vs data.table
AWS Glue DataBrew
aws.amazon.com
data.table
rdatatable.gitlab.ioSide by side
| Figure | AWS Glue DataBrew | data.table |
|---|---|---|
| Price from | $0.48/mo | Free |
| Free plan | — | Yes |
| Free trial | Yes | — |
| Open source | — | — |
| Web | Yes | — |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| API | Yes | — |
| Plans published | 4 | 1 |
| Spec score · Data Transformation Tools | 8.9 (#6) | 8.5 (#11) |
| Integrations | DataBrew datasets can use files, Amazon S3, supported JDBC data sources, or the AWS Glue Data Catalog. | data.table is an R package and can use R functions from other packages in queries. |
| What it does | AWS Glue DataBrew is a visual, fully managed service for cleaning, normalizing and transforming data without writing code. | data.table provides a high-performance version of base R’s data.frame with syntax and feature enhancements. |
Plans
AWS Glue DataBrew
- DataBrew interactive sessions$1 a month
- DataBrew jobs$0.48 a month
- DataBrew interactive sessions$1, paid once
- Pay-as-you-goPriced on request
In their own words
AWS Glue DataBrew
AWS Glue DataBrew has no write-up on Specifiction yet; its figures are above.
data.table
data.table is a free R package providing a high-performance version of base R’s data.frame. Its code interface supports filtering, grouping, aggregation, ordered and rolling joins, overlapping and non-equi joins, reshaping with dcast and melt, and adding, updating, or deleting columns. fread() reads delimited text, including CSV, TSV, compressed .gz and .bz2 files, and can source web URLs or shell commands. fwrite() writes delimited files with an emphasis on speed for large files. Many operations use multiple CPU threads internally. Columns can be changed by reference without copies, and the project reports no external Imports, LinkingTo, or Depends dependencies. Queries can call R functions from other packages. data.table runs on Linux, macOS, and Windows and requires base R. It is self-hosted and licensed under MPL-2.0. The project’s stated scope excludes binary formats such as Parquet and data stored on disk or in remote SQL databases.