Elasticsearch is a tricky, but great data platform
November 09, 2021

Elasticsearch is a tricky, but great data platform

Borislav Traykov | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User

Overall Satisfaction with Elasticsearch

We use Elasticsearch (Elastic for short, but that includes Kibana & LogStash so the full ELK kit) for 3 major purposes:
  • product data persistence - as JSON objects.
  • as log storage - different components produce log files in different formats + logs from other systems like the OSes and even some networking appliances.
  • as test automation results storage & reporting platform - this is an implementation we glimpsed from an old Trivago blog post.
Different forms of Elastic are being used across the company - the vanilla one, OpenDistro and OpenSearch. Licensing limbo + long-term support make people here jump from one implementation to another.
  • Data persistence & retriveval
  • Data indexing
  • Metrics & reporting over data thanks to its query language & Kibana visualization
  • Flexibility of data sources - a lot of existing "beats" + ability to push custom data easily
  • Very scalable - although a minimum of 3 nodes is advised, even a 1-node installation can work great for some use cases.
  • Licensing - this is big issue with a lot of companies that try to embed Elasticsearch as a part of their products and not have to expose that explicitly or deal with licensing complications.
  • Security - this is not a feature enabled by default so installations can go and be unsecure & thus exploited without anyone noticing.
  • Having security turned off can be beneficial for some performance optimizations though.
  • Cluster restructuring/upgrading - if you need to do a rolling cluster upgrade, node roles and data replication is handled in a complicated & tricky way so you need to have knowledge & experience to survive such an operation with your data & cluster to be operational after it.
  • Data persistence, indexing and querying at high speed
  • Scalability
  • Building reporting over data thanks to Kibana
  • Greatly reduced data-in-transit and at-rest overheads
  • Provided us with a truly scalable solution for our data
  • Kibana offers a reporting platform based on our custom queries. Extremely useful for reports from automated test executions.
Elasticsearch is the most well-known and supported free data platform that we identified. We are taking advantage of community knowledge and practices.
In terms of flexibility and breadth of use cases no other competitor came close to Elasticsearch.
We've tried Solr in the past be we encountered issues which were deal-breaking for us.
MongoDB - it just did not pass our evaluation parameters as a main data platform. We still use it for smaller purposes, though.

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Elasticsearch is a really scalable solution that can fit a lot of needs, but the bigger and/or those needs become, the more understanding & infrastructure you will need for your instance to be running correctly.
Elasticsearch is not problem-free - you can get yourself in a lot of trouble if you are not following good practices and/or if are not managing the cluster correctly.
Licensing is a big decision point here as Elasticsearch is a middleware component - be sure to read the licensing agreement of the version you want to try before you commit to it.
Same goes for long-term support - be sure to keep yourself in the know for this aspect you may end up stuck with an unpatched version for years.