Overview
Product Information on Elastic Search
Updated 13th October 2025
What is Elastic Search?
Elastic Search Pricing
Overall experience with Elastic Search
IT Associate
50M - 250M USD, IT ServicesFAVORABLE
“Powerful and scalable search engine with strong indexing capabilities, but requires careful setup and configuration to get the better results.”
Our overall experience has been very positive. We have been using Elastic search engine for our application use cases, mainly for log analytics and content discovery.
It does a great job with indexing and gives us fast search results even when the data grows. The data connectors make it easier to pull in information from different sources, and content processing feature help in preparing and structuring data for search.
The main challenge we faced was the initial setup and configuration. Getting indexing right and handling application integration took some time and effort , and there was a bit of learning curve. Once everything was in place, though, it has been stable and reliable for day-to-day use.
Overall, it's a strong and flexible search engine, just not something you can fully set up without some technical work upfront.
Project Manager
30B + USD, MiscellaneousCRITICAL
“Fast content indexing helps, while app integration needs improvement”
Search is pretty good, as well as the speed at which content is processed
About Company
Company Description
Elastic enables organizations to securely harness search-powered AI so anyone can find the answers they need in real-time using all their data, at scale. By integrating AI with search technology, it facilitates the discovery of actionable insights from large volumes of both structured and unstructured data, addressing the need for real-time, scalable data processing. Our Elasticsearch Platform delivers search-powered AI for observability, security and search. Companies can now solve real-time business problems and achieve better business outcomes by taking advantage of massive amounts of structured and unstructured data, securing and protecting private information more effectively, and optimizing infrastructure and talent resources more efficiently. Elastic’s complete, easy-to-use cloud-based platform offers solutions in search, security, and observability, aimed at aiding businesses in leveraging AI technology securely and effectively.
Company Details
Company type
Public
Year Founded
2012
Head office location
Mountain View, United States
Number of employees
1001 - 5000
Annual Revenue
1B-3B USD
Website
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- IT Associate50M-1B USDIT ServicesReview Source
Powerful and scalable search engine with strong indexing capabilities, but requires careful setup and configuration to get the better results.
Our overall experience has been very positive. We have been using Elastic search engine for our application use cases, mainly for log analytics and content discovery. It does a great job with indexing and gives us fast search results even when the data grows. The data connectors make it easier to pull in information from different sources, and content processing feature help in preparing and structuring data for search. The main challenge we faced was the initial setup and configuration. Getting indexing right and handling application integration took some time and effort , and there was a bit of learning curve. Once everything was in place, though, it has been stable and reliable for day-to-day use. Overall, it's a strong and flexible search engine, just not something you can fully set up without some technical work upfront. - Sdet10B+ USDBankingReview Source
High Performance and Scalability With Elastic Search Offset by Management Challenges
Overall, our experience with Elastic search has been very positive, particularly for implementing enterprise search and real time analytics across large datasets. The platform provides strong indexing and search performance, enabling teams to quickly retrieve and analyze data across multiple sources. As the platform evolves toward AI -powered search capabilities, it provides additional value though semantic search, vector search, and relevance tuning. From an enterprise perspective , it supports a wide range of use cases including observability , log analytics, application search and knowledge discovery. However, successful adoption requires proper architecture planning, cluster management , and governance to ensure performance and cost efficiency at scale. - Business Development Associate<50M USDIT ServicesReview Source
Powerful search platform for large scale backend and log analytics workflows
We mainly use Elasticsearch for log analysis, search heavy workflows and indexing data coming from multiple backend services. Performance has been pretty solid even with large databases and in real time queries as well. Setup and tuning took some effort initially though, especially around mapping and cluster management. It's powerful but not exactly beginner friendly. Once things got stabilized, it becomes core part of monitoring and search flows. - Vp, Engineering50M-1B USDFinance (non-banking)Review Source
Real-time log analytics excel, but high memory use causes instability
Elasticsearch is great for log aggregation from multiple different (legacy mostly) sources. It has incredible horizontal scaling capabilities, and is fantastic for real-time analytics of not-so-clean data. However it requires significant operational overhead to maintain at scale. - CYBERSECURITY ANALYST50M-1B USDRetailReview Source
Robust for security analytics, but setup complexity poses challenges
My overall experience with Elasticsearch has been very positive, particularly for large scale log aggregation, search optimization and security analytics use cases. The platform offers strong performance, flexibility and scalability, making it well suited for cybersecurity operations.
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