Elasticsearch Reviews

165 Ratings
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Score 8.7 out of 100

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Reviews (1-25 of 44)

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June 10, 2021
Keith Lubell | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
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Pros and Cons

  • Indexing text data
  • Aggregations allow users to progressively add search criteria to refine their searches
  • Find trends in our data with Aggregations
  • Integrate text Search our taxonomy Search
  • Joining data requires duplicate de-normalized documents that make parent child relationships. It is hard and requires a lot of synchronizations
  • Tracking errors in the data in the logs can be hard, and sometimes recurring errors blow up the error logs
  • Schema changes require complete reindexing of an index
Read Keith Lubell's full review
April 01, 2021
Josh Kramer | TrustRadius Reviewer
Score 9 out of 10
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Pros and Cons

  • It allows extremely fast search and filtering on large datasets
  • It has a very powerful aggregation engine that can allow for tons of customizable analytics and reports.
  • The documentation could be a bit more detailed and have more examples, especially for advanced functionality.
  • The ability to update/change existing live field mappings would be nice.
  • The ingest pipeline structure is a bit more complicated and confusing than previous implementations for using things like attachment plug-ins.
Read Josh Kramer's full review
January 13, 2021
Swastik Nath | TrustRadius Reviewer
Score 8 out of 10
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Pros and Cons

  • Text-based searches on data
  • Daily, weekly, monthly analytics on data
  • Super easy scripting with painless scripting language
  • Relational data query
  • Sync data from SQL on table change (with hash maybe)
  • Provide better tutorials for beginners
Read Swastik Nath's full review
March 06, 2020
Anonymous | TrustRadius Reviewer
Score 10 out of 10
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Pros and Cons

  • Log storage efficiency - We have millions of events a day and are able to keep 90 days worth for under 1TB of on disk space.
  • Dashboards - Technically through Kibana(but I consider the entire stack as part of Elasticsearch.) Dashboards are easy to manipulate and create from scratch. Many shippers have premade dashboards ready for day one, too.
  • Speed - Have you ever searched an indexed database of 200 million events and found an answer in a matter of seconds? You could with Elasticsearch.
  • Free/self-hosted can be a nightmarish amount of work. When you break it, it's easy to lose data.
  • Documentation is thorough at times, but there still seems to be holes in some components. For instance, PacketBeat doesn't explicitly tell you best practices for DNS logging, and I had to use a different resource to get an answer.
  • Pricing - The free tier is excellent, but it's a significant jump up to get the machine learning modules, endpoint security and more.
Read this authenticated review
December 02, 2019
Mark Freeman, MBA | TrustRadius Reviewer
Score 9 out of 10
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Pros and Cons

  • Search queries based on Java class member names.
  • Very detailed queries through the standard library.
  • Extremely fast.
  • Easy to index.
  • Ability to search content when data only in fields.
  • Query syntax could be made simpler.
  • Auto sharding.
Read Mark Freeman, MBA's full review
November 19, 2019
Erlon Sousa Pinheiro | TrustRadius Reviewer
Score 8 out of 10
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Pros and Cons

  • Centralized logging
  • Easy content searching
  • Handle tons of data
  • Poor documentation
  • Not so easy at the first contact
  • Hard to debugging issues
Read Erlon Sousa Pinheiro's full review
October 09, 2019
Gary Davis | TrustRadius Reviewer
Score 10 out of 10
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Pros and Cons

  • Search results are provided very quickly.
  • The search results are accurate.
  • Search results contain details on the accuracy of each hit.
  • There is a steep learning curve for this product so what is most useful for developers is good documentation including examples and sample applications.
Read Gary Davis's full review
October 26, 2019
Anonymous | TrustRadius Reviewer
Score 9 out of 10
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Pros and Cons

  • As I mentioned before, Elasticsearch's flexible data model is unparalleled. You can nest fields as deeply as you want, have as many fields as you want, but whatever you want in those fields (as long as it stays the same type), and all of it will be searchable and you don't need to even declare a schema beforehand!
  • Elastic, the company behind Elasticsearch, is super strong financially and they have a great team of devs and product managers working on Elasticsearch. When I first started using ES 3 years ago, I was 90% impressed and knew it would be a good fit. 3 years later, I am 200% impressed and blown away by how far it has come and gotten even better. If there are features that are missing or you don't think it's fast enough right now, I bet it'll be suitable next year because the team behind it is so dang fast!
  • Elasticsearch is really, really stable. It takes a lot to bring down a cluster. It's self-balancing algorithms, leader-election system, self-healing properties are state of the art. We've never seen network failures or hard-drive corruption or CPU bugs bring down an ES cluster.
  • Elasticsearch paid support could be much better. Not only is it really expensive, but the reps just don't seem to be that knowledgeable and keep linking us to support documentation we've already found and read.
  • I wouldn't call it missing functionality or a part that's hard to use perse, but upgrading from ES 5 to ES 6 is a PITA. Maaaan did they mess up a part of their data model so bad that when migrating, you have to restructure almost all your queries and transform almost all your data! I don't want to go into too many details here as some people may not be clued in on the concept of mapping types, but you can read more about it here https://www.elastic.co/guide/en/elasticsearch/reference/6.0/breaking-changes-6.0.html.
  • This is no longer a problem in ES 6 but in versions 5 and before, reindexing is a PITA. You have to almost bring down the whole cluster to fix small problems such as missing fields or wrong types.
Read this authenticated review
October 30, 2019
Anonymous | TrustRadius Reviewer
Score 8 out of 10
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Pros and Cons

  • Extremely easy to get started and great documentation.
  • Excellent for full-text use cases.
  • Also used for analytics and Kibana UX is great for visualization.
  • Encountered scaling challenges with large data sets (typically in petabytes).
  • Performance issues for raw aggregation use-cases.
  • Every contract (request/response) is in JSON which is not optimal. No support for protobuffs or GRPC.
Read this authenticated review
June 02, 2019
Jose Adan Ortiz | TrustRadius Reviewer
Score 10 out of 10
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Pros and Cons

  • Anomaly detection. It can find patterns over a wide variety of metrics and values.
  • Behind the walls, Elasticsearch has a robust distributed architecture to support queries and data processing, and it is easy to maintain and scale.
  • Elasticsearch has a new Elastic Cloud SaaS solution which is very easy to deploy, set up, and scale with all features and more.
  • Elasticsearch has an important security layer to separate access to data and dashboards.
  • If you want to explode Elasticsearch's capabilities, you need to have a medium-high SQL and Database knowledge.
  • The user interface is heavy in Java requirements, and sometimes you can get some lag displaying heavy results for heavy queries.
  • It will be helpful if you can construct Logstash queries with a drag&drop based user interface.
Read Jose Adan Ortiz's full review
February 27, 2019
Ben Williams | TrustRadius Reviewer
Score 6 out of 10
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Pros and Cons

  • Powerful beats modules.
  • Later number of input/output pipelines.
  • Open documentation.
  • Documentation is often incomplete.
  • Forums are very full but misleading.
  • The programs don't work well together. They have different methodology and flavors in each.
  • Different configurations in each element make it difficult to use.
Read Ben Williams's full review
October 09, 2018
Anatoly Geyfman | TrustRadius Reviewer
Score 10 out of 10
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Pros and Cons

  • Super-fast search on millions of documents. We've got over 2 billion documents in our index and the retrieve speeds are still in the < 1-second range.
  • Analytics on top of your search. If you organize your data appropriately, Elasticsearch can serve as a distributed OLAP system
  • Elasticsearch is great for geographic data as well, including searching and filtering with geojson, and a variety of geospatial algorithms.
  • Elasticsearch is highly distributed, but it takes time to tune so you get the right performance out of your cluster.
  • The query language is not SQL, so it's not a straightforward conversion from an RDBMS to Elasticsearch for searching through data.
  • There are lots of ways to insert data into Elasticsearch, and some are better than others (batch vs. single insert). Need to experiment with your own data and environment.
Read Anatoly Geyfman's full review
October 08, 2018
Tarun Mangukiya | TrustRadius Reviewer
Score 10 out of 10
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Verified User
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Pros and Cons

  • Fast Search through millions of data
  • Uses a very limited storage to store the data - high compression
  • Easy to get started & configure
  • Their documentation needs a lot of imporvement
  • Difficult to understand query language
  • New updates are difficult to adopt
Read Tarun Mangukiya's full review
April 13, 2018
Brett Knighton | TrustRadius Reviewer
Score 8 out of 10
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Pros and Cons

  • The best solution we've found for blazing fast searches, especially text-based.
  • Easy to add nodes for data redundancy.
  • Good documentation makes getting up and running easy.
  • I found the learning curve fairly difficult having a SQL background.
Read Brett Knighton's full review
March 01, 2018
David Greenwell | TrustRadius Reviewer
Score 10 out of 10
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Verified User
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Pros and Cons

  • Searching, it does it well and searches are fast...real fast.
  • Ease of use, we were able to get an Elasticsearch cluster up and running in a half hour and doing basic searches after that was very easy with simple requests
  • Redundancy built in and stability. We haven't had any of our Elastic clusters go down intentionally, but testing out redundancy by removing nodes Elasticsearch has gone flawlessly.
  • Only breaking changes between versions when they are absolutely necessary.
  • Works well with .Net libraries that are supported and coded by Elastic.
  • A bit more of a learning curve for complex searches, indexing more complex things.
  • Some of our updates between versions haven't gone as smoothly as we would like, but in more recent versions Elastic has done a much better job at trying to allow for full uptime upgrades.
  • Configuration needs to be set up to do larger searches, or more complex searches and at times while starting it wasn't obvious what configuration needed to be changed.
Read David Greenwell's full review
August 31, 2017
Colby Shores | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
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Pros and Cons

  • Effortless to set up. Literally set the memory thresholds for Java and start throwing JSON formatted records in to the database, it "Just Works". Even clustering is automated as the cluster finds other ElasticSearch servers on the network and assigns each a name.
  • Very simple to use interface either through it's RESTFUL API (ala Curl) or via its speedy protocol on port 9300. Once records are added, the very easy to use Apache Lucene syntax is supported to extract data.
  • It's search capabilities are fast on huge datasets, even on very modest hardware. Our organization operates in the hundreds of servers taking thousands of requests a second, each with it's own log w/ a 2 week retention. The ElasticSearch server we recently decommissioned was Pentium 4 Netburst class Xeon, it rarely skipped a beat.
  • Setting Java memory thresholds can be a pain for those not accustomed to things like Eden Space & Old Generation which can lead to over allocation, or more likely, under allocation. Apache Solr had a similar issue. It would be nice if the program would take an extra step and dogfood it's own advice by analyzing the system & processes to return a solid recommendation for that configuration. The proper configuration information is outlined in the documentation, it would be nice if that was automated.
  • The only health check that ElasticSearch reports back is a "red" status without any real solid information about what is going on, though its usually memory thresholds or disk I/O. I am currently on ElasticSearch 1.5 so that may have changed for newer versions. When the status goes "red", I as the administrator of the software, feel like I lose control of whats going on which should rarely happen. Something more verbose would eliminate that.
  • This is more of a critique of the ElasticStack in general. The whole top to bottom stack is starting to get feature creep with things that are better suited in other software and increasing the barrier for entry for people to get started with setting up a robust logging infrastructure. ElasticSearch as a storage search engine, is pretty streamlined, but I can see that the tools that comprise the ELK Stack are going to require a certification with constant study at some point. During major release for Logstash a while back, it literally took a month to learn a new language because Elastic completely changed the syntax. For a medium sized organization of only a couple of admins, that is a pretty high bar where time is money. They really should work on refining/automating the tools & search engine they have, instead of shoehorning/changing things on to an already rock solid foundation.
Read Colby Shores's full review
November 14, 2017
Trung Le | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source

Pros and Cons

  • Comprehensive reports and queries
  • Data analytics
  • A better way to provide custom functions. I struggled with implementing the PercentileExc (exlusive) funtion, the one that Excel provided, because the business users requested it.
  • Better IntelliSense in development console, when the query is complex, I often lost the IntelliSense feature. The “exists” query is not supported by IntelliSense.
Read Trung Le's full review
October 04, 2017
Manish Rajkarnikar | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
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Pros and Cons

  • Elasticsearch search with its clustering solution provides a scalable logging solution. A number of query nodes, data node and master node can be added on demand to make the whole system very scalable making it possible to store and search terabytes of data.
  • Elasticsearch provides logstash, file beat, and many others. It makes it really easy to ingest a log with less setup.
  • Elasticsearch query language is based on Lucene and is very powerful.
  • Elasticsearch is mostly free except a few features such as authentication and authorization; making it really financially economical for companies to deploy it on large scale.
  • Elasticsearch doesn't have a free alerting solution. It has elastalert but it's not comparable to the paid version.
  • It's lacking authentication and authorization which makes Graylog a more enticing option.
  • It's lacking a mechanism to protect cluster against runoff queries. Can bring down cluster to its knees.
Read Manish Rajkarnikar's full review
April 04, 2017
Kris Bandurski | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
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Pros and Cons

  • 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.
Read Kris Bandurski's full review

What is Elasticsearch?

Elasticsearch is an enterprise search tool from Elastic in Mountain View, California.
Categories:  Enterprise Search

Elasticsearch Pricing

  • Does not have featureFree Trial Available?No
  • Does not have featureFree or Freemium Version Available?No
  • Does not have featurePremium Consulting/Integration Services Available?No
  • Entry-level set up fee?No
EditionPricing DetailsTerms
Standard$16.00per month
Gold$19.00per month
Platinum$22.00per month
EnterpriseContact Sales

Elasticsearch Technical Details

Deployment Types:SaaS
Operating Systems: Unspecified
Mobile Application:No

Frequently Asked Questions

What is Elasticsearch?

Elasticsearch is an enterprise search tool from Elastic in Mountain View, California.

What is Elasticsearch's best feature?

Reviewers rate Support Rating highest, with a score of 7.6.

Who uses Elasticsearch?

The most common users of Elasticsearch are from Mid-size Companies and the Computer Software industry.