aws-data-wrangler VS prose

Compare aws-data-wrangler vs prose and see what are their differences.

aws-data-wrangler

pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL). [Moved to: https://github.com/aws/aws-sdk-pandas] (by awslabs)

prose

:book: A Golang library for text processing, including tokenization, part-of-speech tagging, and named-entity extraction. (by jdkato)
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aws-data-wrangler prose
1 1
3,559 2,924
- -
10.0 1.9
9 months ago almost 2 years ago
Python Go
Apache License 2.0 MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

aws-data-wrangler

Posts with mentions or reviews of aws-data-wrangler. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-08-20.

prose

Posts with mentions or reviews of prose. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-03-27.
  • Go+: Go designed for data science
    5 projects | news.ycombinator.com | 27 Mar 2021
    Apart from Gonum[1] numerical libraries, I haven't found specific data science related Go libraries in my search for it for some hobby projects when compared to Python ecosystem.

    Interestingly Prose[2] A Go library for text processing yielded better results for named-entity extraction when compared to NLTK in my tests in terms of accuracy and obviously performance.

    Perhaps Go is not being applied enough in the Data Science/ML and for fields where it's applied (Network) Math in the standard library seems to be sufficient.

    [1] https://github.com/gonum/gonum

    [2] https://github.com/jdkato/prose

What are some alternatives?

When comparing aws-data-wrangler and prose you can also consider the following projects:

boto3 - AWS SDK for Python

gse - Go efficient multilingual NLP and text segmentation; support English, Chinese, Japanese and others.

Trapheus - This tool automates restoration of RDS database instances from snapshots into any dev, staging or production environments. It supports individual RDS Snapshot as well as cluster snapshot restore operations.

go-i18n - Translate your Go program into multiple languages.

Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

textcat - A Go package for n-gram based text categorization, with support for utf-8 and raw text

ray_snowflake - Ray Data Connector for Snowflake

porter2 - High Performance Porter2 Stemmer

demo-code - Bits of code I use during live demos

gojieba - "结巴"中文分词的Golang版本

aws-simple-websocket - Using AWS's API Gateway + Lambda to run a simple websocket application. For learning/testing.

go-mystem - CGo bindings to Yandex.Mystem