Overall Satisfaction with Elasticsearch
Elasticsearch is currently in our organization for multiple use cases. With the data volume growing huge and rapidly, we push the data into an Elasticsearch cluster setup. We collect logs from multiple systems and push into E C using logstash and few other message brokers system. We collect telemetry from multiple systems and run algorithms to analyze the data.
- Indexing
- Text analysis
- Time series data handling
- Connector to other big data software
- Plugins to visualize the data other than Kibana
- Better query editor
- Server cost and infrastructure management became easy.
- Efficiency in data handling.
- Less development time.
- Apache Solr and MongoDB
Elasticsearch is DevOps friendly; it is easy for installation and management of a node/cluster. It is very friendly for developers by providing the REST API out of the box, reducing the development time.