Amazon Comprehend vs Google Cloud Natural Language API

Need advice about which tool to choose?Ask the StackShare community!

Amazon Comprehend

45
116
+ 1
0
Google Cloud Natural Language API

39
111
+ 1
0
Add tool

Amazon Comprehend vs Google Cloud Natural Language API: What are the differences?

Developers describe Amazon Comprehend as "Discover insights and relationships in text". Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to discover insights from text. Amazon Comprehend provides Keyphrase Extraction, Sentiment Analysis, Entity Recognition, Topic Modeling, and Language Detection APIs so you can easily integrate natural language processing into your applications. On the other hand, Google Cloud Natural Language API is detailed as "Derive insights from unstructured text using Google machine learning". You can use it to extract information about people, places, events and much more, mentioned in text documents, news articles or blog posts. You can use it to understand sentiment about your product on social media or parse intent from customer conversations happening in a call center or a messaging app. You can analyze text uploaded in your request or integrate with your document storage on Google Cloud Storage.

Amazon Comprehend and Google Cloud Natural Language API can be categorized as "NLP / Sentiment Analysis" tools.

Get Advice from developers at your company using Private StackShare. Sign up for Private StackShare.
Learn More
Cons of Amazon Comprehend
Cons of Google Cloud Natural Language API
  • 2
    Multi-lingual
  • 2
    Multi-lingual

Sign up to add or upvote consMake informed product decisions

What is Amazon Comprehend?

Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to discover insights from text. Amazon Comprehend provides Keyphrase Extraction, Sentiment Analysis, Entity Recognition, Topic Modeling, and Language Detection APIs so you can easily integrate natural language processing into your applications.

What is Google Cloud Natural Language API?

You can use it to extract information about people, places, events and much more, mentioned in text documents, news articles or blog posts. You can use it to understand sentiment about your product on social media or parse intent from customer conversations happening in a call center or a messaging app. You can analyze text uploaded in your request or integrate with your document storage on Google Cloud Storage.

Need advice about which tool to choose?Ask the StackShare community!

What companies use Amazon Comprehend?
What companies use Google Cloud Natural Language API?
See which teams inside your own company are using Amazon Comprehend or Google Cloud Natural Language API.
Sign up for Private StackShareLearn More

Sign up to get full access to all the companiesMake informed product decisions

What tools integrate with Amazon Comprehend?
What tools integrate with Google Cloud Natural Language API?
What are some alternatives to Amazon Comprehend and Google Cloud Natural Language API?
IBM Watson
It combines artificial intelligence (AI) and sophisticated analytical software for optimal performance as a "question answering" machine.
SpaCy
It is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest research, and was designed from day one to be used in real products. It comes with pre-trained statistical models and word vectors, and currently supports tokenization for 49+ languages.
rasa NLU
rasa NLU (Natural Language Understanding) is a tool for intent classification and entity extraction. You can think of rasa NLU as a set of high level APIs for building your own language parser using existing NLP and ML libraries.
Gensim
It is a Python library for topic modelling, document indexing and similarity retrieval with large corpora. Target audience is the natural language processing (NLP) and information retrieval (IR) community.
Transformers
It provides general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet…) for Natural Language Understanding (NLU) and Natural Language Generation (NLG) with over 32+ pretrained models in 100+ languages and deep interoperability between TensorFlow 2.0 and PyTorch.
See all alternatives