Amazon OpenSearch Service Reviews

I use it for database. For RAG, you need a vector store to store embeddings.

To store the vectors, you need embedding models to convert the data into vectors. You then need to store those vectors in any vector store. Popular ones are like Chroma DB. 

As a new alternative, I selected OpenSearch, which falls under the whole AWS infrastructure. So to bring our full architecture into AWS, I use OpenSearch as a service as my vector store.

It is effective for data analysis. This service already sorts data like vectors. They have classified the storage pre-defined. We just need to select the purpose of the data, like time series data or vectors. It will be as effective as any other DVR or vector tool. 

We need to retrieve data and implement our tools or libraries for analysis. The scalability is good; they use a serverless solution, so we don't need to worry about it.

Security features:

Security is decent, but there aren't enough security features. I don't see any built-in authentication functions. However, there is an option to enable or disable the public or private subnet like other AWS services. So, we can make the dashboard public or private. Using AWS signer, you can sign in with AWS tokens.

OpenSearch is used as a search engine for specific logs, mainly in e-commerce and monitoring the logs themselves. It is very valuable for e-commerce, enabling data analysis on application logs and customer behavior, and can be integrated with other services, including AI and machine learning algorithms.

OpenSearch provides data for AI solutions. It allows integration with machine learning algorithms to extract recommendations and insights, enhancing our ability to train models and produce valuable recommendations.

I primarily use Amazon OpenSearch Service for log management and data storage. It's used to store third-party data and manage large volumes of query data across various services, including AWS Lambda and Kubernetes.

Amazon OpenSearch Service has enhanced our organization's ability to store and search large amounts of data efficiently. 

Transitioning from Amazon CloudWatch to Amazon OpenSearch Service for logging helped decrease costs since handling high volumes of logs was less expensive.

We use the solution as a login platform. We have a lot of microservices, and we get log records from there, which we host on Amazon OpenSearch.

There are a couple of cool features. The service provides vacuum storage for cold or ultra-warm data. We retrieve historical data with just a click of a button to move it from cold to hot or warm because it's already stored in the backend storage, S3.