G2

Salman K.

Staff Engineer

Mid-Market (51-1000 emp.)

9/29/2026

"Powerful distributed search and centralized log analytics engine"

4.5/5

What do you like best about Elasticsearch?

It handles massive, high-throughput log volumes effortlessly and delivers impressive query speed. The Lucene-based inverted index enables near-instant full-text search across distributed indices. It also integrates smoothly into standard observability setups like Fluentbit, Logstash, and Kibana, which makes log aggregation, indexing, and visualization straightforward to implement. Review collected by and hosted on G2.com.

What do you dislike about Elasticsearch?

JVM garbage collection tuning and memory overhead can get tricky, especially under heavy indexing loads. If mappings aren’t optimized or you run into field explosions, heap usage can balloon fast and push the cluster toward instability. On top of that, managing index lifecycles, shard allocation, and storage retention takes ongoing operational attention and effort to keep everything running smoothly. Review collected by and hosted on G2.com.

What problems is Elasticsearch solving and how is that benefiting you?

It centralizes application and infrastructure logging, giving us a true single pane of glass for observability across distributed systems. During outages, it significantly reduces mean time to resolution (MTTR) by enabling fast, structured queries across millions of log records. It also delivers reliable, low-latency search for our custom data stores, so we can query what we need without putting load on our primary relational databases. Review collected by and hosted on G2.com.