I think this question is valuable and a familiar question is here. And for your use cases Elasticsearch has many extra tools. See the list.
In my case; Elasticsearch + Kibana stack is great to store logs. You can visualize and monitor your logs with Kibana.
And secondly utilizing it, as a search engine. Elasticsearch is a full-text search engine and it's easy to combine with relational databases or other graph databases.
Elasticsearch introduction says:
- Add a search box to an app or website
- Store and analyze logs, metrics, and security event data
- Use machine learning to automatically model the behavior of your data in real time
- Automate business workflows using Elasticsearch as a storage engine
- Manage, integrate, and analyze spatial information using Elasticsearch as a geographic information system (GIS)
- Store and process genetic data using Elasticsearch as a bioinformatics research tool
In other words, a database is for retrieving and managing data. But Elastic stack is used for searching and analytics.
This competitive chart may help you to identify the roles in a project.
https://db-engines.com/en/system/Elasticsearch%3BGraph+Engine%3BNeo4j