Developer's Elasticsearch Review
Devaraj Natarajan profile photo
September 15, 2017

Developer's Elasticsearch Review

Score 7 out of 10
Vetted Review
Verified User
Review Source

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.
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.
I have noticed Elasticsearch is good in following scenarios:
Faster Aggregation
Full-text search features
Scalable
Great performance
Stability
Complete Ecosystems of applications

It could have been slightly better in handling indexing. (Should index all the items and create index overhead)
Better load balancing
Elasticsearch aggregations are not always precise, because of how data in the shards is placed