Elasticsearch

Elasticsearch

About TrustRadius Scoring
Score 8.3 out of 100
Elasticsearch

Overview

Recent Reviews

Win quickly with Elasticsearch

8 out of 10
October 30, 2019
Elasticsearch is used as a full-text search solution in most of my use cases. We have another analytics us -case which uses Elasticsearch …
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Elasticsearch is the future!

9 out of 10
October 26, 2019
The most crucial piece of infrastructure behind my company's whole product line is Elasticsearch. Our company's big selling point is an …
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Awards

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Pricing

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Standard

$16.00

Cloud
per month

Gold

$19.00

Cloud
per month

Platinum

$22.00

Cloud
per month

Entry-level set up fee?

  • No setup fee

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting / Integration Services
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Features Scorecard

No scorecards have been submitted for this product yet..
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Product Details

What is Elasticsearch?

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

Elasticsearch Technical Details

Deployment TypesSaaS
Operating SystemsUnspecified
Mobile ApplicationNo

Frequently Asked Questions

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

Reviewers rate Support Rating highest, with a score of 7.8.

The most common users of Elasticsearch are from Enterprises (1,001+ employees) and the Computer Software industry.
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Comparisons

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Reviews and Ratings

 (192)

Ratings

Reviews

(1-25 of 46)
Companies can't remove reviews or game the system. Here's why
Borislav Traykov | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
  • 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.
Keith Lubell | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
  • 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
April 01, 2021

Elasticsearch Review

Josh Kramer | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
  • 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.
Score 10 out of 10
Vetted Review
Verified User
Review Source
  • 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.
Score 8 out of 10
Vetted Review
Verified User
Review Source
  • 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.
Score 9 out of 10
Vetted Review
Verified User
Review Source
  • 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.
Gary Davis | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
  • 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.
Score 9 out of 10
Vetted Review
Verified User
Review Source
  • It's an Open Source tool
  • Elasticsearch extends its visualization and analytics capabilities through Kibana, which is a powerful tool
  • Elasticsearch provides 3rd party integration facilities using REST API
  • Search capabilities can be further improved with a much faster response time on historical logs
  • Elasticsearch should have a phone/sms alert feature as well as an event trigger
  • Learning guides could be more detailed
Jose Adan Ortiz | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
  • 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.
Score 9 out of 10
Vetted Review
Verified User
Review Source
  • Easy to install
  • Easy to use/lots of documentation
  • Easy to scale up as demand increases
  • The price point for the X-Pack plugins (ie. Security, Alerting, etc.) is a bit high, especially if you only want to do something small and simple and you don't need to leverage the full power of the plugin
  • Configuring the right hardware and capacity planning (when at scale) can get really tricky. In order to get the best performance, a lot of tweaking is needed, and not all of the secret tricks are documented
  • Getting used to ElasticSearch's query language was a bit of an adjustment. You really have to delve into defining analyzers and tokenizers in order to get application-specific results
Ben Williams | TrustRadius Reviewer
Score 6 out of 10
Vetted Review
Verified User
Review Source
  • 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.
Score 7 out of 10
Vetted Review
Verified User
Review Source
  • Free of SQL: ES does not have the overhead of relying on SQL. In fact, you can use most (if not all) DBMs out there.
  • Java: Normally, this is not a strength: Java is slow and cumbersome. I believe in this case, it's truly a feature: by utilizing a language with universal support, it makes ES VERY DevOps friendly, simply by being able to focus on Problem-oriented vs Solutions-based thinking.
  • Although ES has been known to consume RAM, it's very flexible, and I have implemented on a number of distinct hardware configuration with success.
  • Linux: It's not locked down to an OS (which is the way of the future), and as a result-running it on Linux means you get the power of Linux, in a data science package.
  • Elastic Search IS a resource hog: most of the time, I will run ES on a dedicated VM (often a dedicated blade, too!) and allow the other components of the stack to run on separate blades/VMs.
  • Works great for small projects, but is NOT industrial strength: When you are performing a data architecture project, where you are capturing and mining datasets, ES is fine, until you start getting into much denser data sources (orders to TBs), such that ES will violate Data integrity.
  • It only supports JSON output: Which is very friendly to a lot of DevOps/Data Architecture projects but may become a hassle when your endpoints require CVS, XML, etc.
January 10, 2019

The Best Available

Score 9 out of 10
Vetted Review
Reseller
Review Source
  • Search
  • Correlation
  • Analysis
  • Big data
  • Pagination
  • Presentation
  • Mapping
Score 10 out of 10
Vetted Review
Verified User
Review Source
  • Lightning fast
  • Easily scalable
  • Powerful feature set
  • Additional complexities when in need of frequent & rapid updates to the Elasticsearch data set
  • New syntax can be confusing, particularly with advanced features and more powerful queries
Anatoly Geyfman | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
  • 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.
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