Find things with Elasticsearch
April 04, 2017
Find things with Elasticsearch
Score 10 out of 10
Vetted Review
Verified User
Overall Satisfaction with Elasticsearch
The first use case is log aggregation. We have a number of micro-services running, some of them in Docker, and we use the ELK to ensure we have easy access to our most recent logs. This proves invaluable for fault detection and diagnosis and is used primarily by engineers. Another use case in a customer-centric search index. Each of our customers is described by a set of data points that come from various sources and are indexed in Elasticsearch. The index is later used by marketing, customer service, and other departments to get quick insights on our customer base.
- Flexible and advanced search.
- Ease of creating time-based indices and automatic archiving of old indices.
- Quick data ingestion.
- Configuration. Looking forward to seeing Elasticsearch detecting hardware specs and self-adjusting its config.
- The lack of _changes streams. They were promised to appear in 2.0...
- The price of the hosted solution could be lower.
- Sped up fault detection, diagnosis and recovery.
- Facilitated getting insights on customer base.
- Helped implement data-driven approach across the whole business.
- Solr
I have used Solr only briefly, but Elasticsearch wins when it comes to the ease of setting up and getting access to data stored in search indices (Kibana). It also comes with comprehensive and easy to read documentation that familiarises the reader with the concepts behind a distributed search engine.