Skip to main content
TrustRadius
Elasticsearch

Elasticsearch

Overview

What is Elasticsearch?

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

Read more
Recent Reviews

TrustRadius Insights

Elasticsearch has become an essential tool for users across various industries and domains. Its distributed architecture enables efficient …
Continue reading
Read all reviews

Awards

Products that are considered exceptional by their customers based on a variety of criteria win TrustRadius awards. Learn more about the types of TrustRadius awards to make the best purchase decision. More about TrustRadius Awards

Reviewer Pros & Cons

View all pros & cons
Return to navigation

Pricing

View all pricing

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
Return to navigation

Product Demos

How to create data views and gain insights on Elastic

YouTube

Setting Up a Search Box to Your Website or Application with Elasticsearch

YouTube

ChatGPT and Elasticsearch: OpenAI meets private data setup walkthrough

YouTube
Return to navigation

Product Details

What is Elasticsearch?

Elasticsearch is a distributed, RESTful search and analytics engine capable of addressing a growing number of use cases. As the heart of the Elastic Stack, it centrally stores data for fast search, fine‑tuned relevancy, and analytics that scale.

Elasticsearch now features generative AI search capabilities. Elasticsearch Relevance Engine™ (ESRE) powers generative AI solutions for private data sets with a vector database and machine learning models for semantic search that bring increased relevance to more search application developers.

ESRE combines AI with Elastic’s text search to give developers a full suite of sophisticated retrieval algorithms and the ability to integrate with large language models (LLMs). It is accessed through a single, unified API.

The Elasticsearch Relevance Engine’s configurable capabilities can be used to help improve relevance by:

  • Applying advanced relevance ranking features including BM25f, a critical component of hybrid search
  • Creating, storing, and searching dense embeddings using Elastic’s vector database
  • Processing text using a wide range of natural language processing (NLP) tasks and models
  • Letting developers manage and use their own transformer models in Elastic for business specific context
  • Integrating with third-party transformer models such as OpenAI’s GPT-3 and 4 via API to retrieve intuitive summarization of content based on the customer’s data stores consolidated within Elasticsearch deployments
  • Enabling ML-powered search without training or maintaining a model using Elastic’s out-of-the-box Learned Sparse Encoder model to deliver highly relevant, semantic search across a variety of domains
  • Combining sparse and dense retrieval using Reciprocal Rank Fusion (RRF), a hybrid ranking method that gives developers control to optimize their AI search engine to their unique mix of natural language and keyword query types
  • Integrating with third-party tooling such as LangChain to help build sophisticated data pipelines and generative AI applications

Elasticsearch Video

What is Elasticsearch?

Elasticsearch Technical Details

Deployment TypesSoftware as a Service (SaaS), Cloud, or Web-Based
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).
Return to navigation

Comparisons

View all alternatives
Return to navigation

Reviews and Ratings

(205)

Community Insights

TrustRadius Insights are summaries of user sentiment data from TrustRadius reviews and, when necessary, 3rd-party data sources. Have feedback on this content? Let us know!

Elasticsearch has become an essential tool for users across various industries and domains. Its distributed architecture enables efficient searching of large datasets, even with partial text matches and across multiple fields. This capability makes it invaluable for tasks such as logging and analysis in cloud environments, where managing hundreds or thousands of servers is a necessity. Elasticsearch's fast and powerful search capabilities find application in B2B and B2C eCommerce websites, allowing users to search by various criteria like title, artist, genre, price range, and availability date. It serves as a reliable solution for tracking logs, incidents, analytics, and code quality. Additionally, Elasticsearch's ability to index and search large sets of data facilitates the creation of reporting dashboards. The product's built-in data replication features ensure data availability and easy retrieval while its scalability supports operational needs. It also enables tokenized free text search in audio transcripts as well as indexing and analyzing HTTP Request Response messages to detect security threats. With its wide range of use cases spanning from web search engines to scientific journals and complex data indexing, Elasticsearch proves to be an indispensable tool for organizations seeking efficient data storage solutions.

Highly Scalable Solution: Elasticsearch has been consistently praised by users for its highly scalable nature. It is able to handle storing and retrieving large numbers of documents, offering redundancy and distributed storage across multiple hosts with minimal configuration required.

Extensive Search Capabilities: Users highly praise Elasticsearch for its extensive search capabilities, especially in terms of full-text search. They find it easy to search and filter through millions of documents efficiently, even on large datasets, thanks to its fast search speeds.

Valuable Aggregations and Facets: Elasticsearch's support for aggregations and facets is highlighted as a valuable feature by users. They appreciate the ability to progressively add search criteria to refine their searches and uncover trends in their data.

Configuration Process: Users have encountered difficulties when implementing custom functions and have found the configuration process to be lacking. Some reviewers have mentioned challenges in integrating different elements of the program, incomplete documentation, and misleading forums.

Query Editor Limitations: Users have experienced issues with the query editor and noted that certain queries are not supported in the IntelliSense feature. Several users expressed frustration with inadequate documentation, hard-to-debug problems, and the complexities involved in tuning for ingress performance.

Learning Curve: Users have found the learning curve to be challenging, particularly for those with a background in SQL. Many reviewers mentioned a steep learning curve, extensive documentation requirements, and complexities related to mapping and data type conversion.

Attribute Ratings

Reviews

(1-25 of 47)
Companies can't remove reviews or game the system. Here's why
John Anderson | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
As stated before, it does a good job of providing analysis and visualization on data coming into the system, but troubleshooting could be better (when issues arise). Performance, scalability, and overall speed are good, but the trade-off is it can be resource-intensive. Overall a good tool, it just takes a bit to learn (it's not always as "intuitive" as it should be).
Borislav Traykov | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
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.
Oscar Narváez Del Rio | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Incentivized
Elasticseach platform allows implementing a robust operational stuck for unified observability handling a huge volume of data with high performance and capacity to scale fast. Logstash, Beats, and APM products provide a structured framework to collect events and data being easy to deploy and configure.
Keith Lubell | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Incentivized
Elasticsearch is really well suited for searching text (Natural Language Processing) and you can fine tune the searches and scoring very well. I like the ability to find Significant Terms in the Index, where you can find aggregations that are really relevant to a specific search. It also allows for queries to lead to new queries via aggregations which is great for navigating your data. It is less suited to doing more complex aggregations where slices of data are required to be processing using guassian normalizations. And doing searches which join different documents is very very hard, and requires serious thought on how to denormalize data.
Andrew Meyer | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Elasticsearch is used very well in the log management space. In conjunction with Logstash, Kibana, and Graylog Elasticsearch makes leveraging these products wonderful. The ease of deploying it. Securing it very quickly. Fast and scalable searching options. It can also be a distributed data warehouse for immutable documents. However, it is not a fully functional database system.
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Elasticsearch is best suited for search, analytics, aggregation, and consumption from single tabular structured data. It works best if you sync your data at regular intervals either with Logstash or any other custom sync process.

However, Elasticsearch still does not support relational queries out of the box. You could denormalize your data before every sync, but that has the potential for complicating the sync process very fast.
Score 10 out of 10
Vetted Review
Verified User
Incentivized
Easiest recommendation of my career. The capability and speed are out of this world, and pricing compared to enterprise logging solutions is a fraction of the cost. That'd come with a caveat, that you must be ready to devote some time to it to learn it and get it working. It's not turnkey, but it's one of the best all-around.
Score 7 out of 10
Vetted Review
Verified User
Incentivized
Elasticsearch is very well suited within an IT architecture where a lot of open-source software is already being used and where the developers strongly appreciate open-source software. Elasticsearch might be less appropriate in an organisation where there is less space to master the tool. The tool is quite difficult to learn once you start working on the CLI-level search queries.
Maria Sousa | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Elasticsearch really excels in search performance, so if you have massive amounts of data you need to search from, Elasticsearch is surely a great fit. I woud advise against using it as the main database or the only source of truth, because data corruption can happen in rare cases, and in that case a reindexing will have to take place.
Erlon Sousa Pinheiro | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Elasticsearch is a great tool, but remember as every other tool, needs knowledge and expertise to work with. My first option would be using the cloud version provided by Elastic company, but unfortunately it is over my budget, then I need to manage by myself. Also according to your company's area, it wouldn't be possible to keep your data into third's cloud environment. In this case, there is no option other than keeping it by yourself.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Elasticsearch's best use case is when you want to store loosely-structured data and be able to search for it near-instantly. And you want to do that in a highly tolerant distributed system. My company doesn't use it this way but I've heard of other companies using ES to store system logs. Another company uses it to store giant store-catalogs.
Gedson Silva | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Elasticsearch is so versatile and so easy to set up that it's really a no-brainer including it in most projects as the indexing and search engine components, as well as for analytics and aggregations. It's not so well-suited to be used as the main database, as there's a minor risk of data loss.
Jose Adan Ortiz | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Incentivized
Elasticsearch can be used perfectly inside a site for searching features in order to respond quickly to user queries. It can be used to act as a Centralized Log Server, where you can define events based on pattern detection for anomaly detection.
Elasticsearch has potent visualization features with Canvas and OOB Dashboards that can respond to business and technical requirements.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
ElasticSearch is great when you need a lot of data indexed really fast, as well as when you need to retrieve a large number of documents based on a complex query. Searching is super-fast.

If you need a large data store for documents where not everything needs to be indexed, don't use JUST ElasticSearch. We use one KV database system to store all of our data and use ElasticSearch as our Index. All searches are run off of ElasticSearch, and the main data store that it pulls from is the other database.
Score 7 out of 10
Vetted Review
Verified User
Elasticsearch is great for development/research projects: It's fast, and *fairly* simple to set up. Project ideas of the calibre of: Watching a marketing feed from Twitter, or scraping sites. But for High availability in (say) a SCADA environment, probably not helpful. Though, I would recommend it for logging system nodes: such as a data center, trouble ticketing dashboard, or health/status visualizations.
January 10, 2019

The Best Available

Score 9 out of 10
Vetted Review
ResellerIncentivized
Elasticsearch is a great fit for a data lake environment that is being created to get rid of the typical siloed environment in so many data centers today. Being able to easily search, analyze, and correlate device information in easy to read JSON files is crazy valuable to our internal team.
Score 10 out of 10
Vetted Review
Verified User
Incentivized
Elasticsearch is the gold standard for text-based search. Across large data sets it performs admirably, and we will certainly make it our first choice search solution in the future. For a use case where needs are simple and regular database queries might suffice, Elasticsearch may or may not provide any benefits.
Anatoly Geyfman | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Incentivized
Elasticsearch is extremely well suited for structured (faceted) search, full-text search, and analytics workloads. Elasticsearch and the ELK stack are also a good fit for operations teams that want to be able to interrogate their logs in an online (read: fast) query tool. Elastic is amazing at creating super fast search experiences over very large datasets, where traditional RDBMS systems are either too costly or too slow.
Return to navigation