Amazon Elasticsearch Service vs rasa NLU: What are the differences?

# Introduction
The following points outline key differences between Amazon Elasticsearch Service and Rasa NLU.

1. **Hosting**: Amazon Elasticsearch Service provides a managed service for deploying Elasticsearch clusters on AWS infrastructure, while Rasa NLU is an open-source library for natural language understanding that can be deployed on any platform.
   
2. **Use Case**: Amazon Elasticsearch Service is primarily used for full-text search and analytics on large datasets, whereas Rasa NLU is designed specifically for building conversational AI applications by understanding and extracting meaning from text inputs.

3. **Scalability**: Amazon Elasticsearch Service offers scalable infrastructure with built-in features for high availability and performance tuning, while Rasa NLU requires manual configuration and deployment for scaling capabilities.

4. **Cost**: Amazon Elasticsearch Service involves costs for infrastructure, storage, and processing power, while Rasa NLU is free to use and can be deployed without additional cost on most platforms.

5. **Customization**: Amazon Elasticsearch Service provides built-in integrations with other AWS services for additional functionality, whereas Rasa NLU allows for extensive customization through the development of custom machine learning models and pipelines.

6. **Deployment Flexibility**: Amazon Elasticsearch Service is tightly coupled with AWS ecosystem and may require specific configurations for integration, while Rasa NLU can be integrated with various platforms and services due to its open-source nature and flexibility. 

In Summary, Amazon Elasticsearch Service and Rasa NLU differ in areas such as hosting, use case, scalability, cost, customization, and deployment flexibility.