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Amazon Elasticsearch Service

Amazon Elasticsearch Service

Overview

What is Amazon Elasticsearch Service?

Amazon Elasticsearch Service is a fully managed service that enables users to search, analyze, and visualize your log data at petabyte-scale. As a fully managed service, Amazon Elasticsearch Service manages the setup, deployment, configuration, patching, and monitoring of Elasticsearch clusters,…

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Pricing

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What is Amazon Elasticsearch Service?

Amazon Elasticsearch Service is a fully managed service that enables users to search, analyze, and visualize your log data at petabyte-scale. As a fully managed service, Amazon Elasticsearch Service manages the setup, deployment, configuration, patching, and monitoring of Elasticsearch clusters, so…

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  • Premium Consulting/Integration Services

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What is Elasticsearch?

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

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Product Details

What is Amazon Elasticsearch Service?

Amazon Elasticsearch Service Technical Details

Operating SystemsUnspecified
Mobile ApplicationNo
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Reviews and Ratings

(13)

Reviews

(1-4 of 4)
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Sunny Hemnani | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
1. With Amazon Elasticsearch Service, we analyze logs of our microservices-based application to fix bugs. 2. With Amazon Elasticsearch Service, we accumulate data across the microservices of our product for visualization & other business purposes. 3. The benefit of elastic search is that, since data is in JSON format, all our microservices can easily change the data structure.
  • Fast Index based search.
  • Scalable.
  • Best for structured and unstructured data.
  • It is not so simple to learn.
  • Documentation is often very confusing.
Supports geographical data for location-based search where Amazon Elasticsearch Service is suited best. Amazon Elasticsearch Service provides various text analysis functionality for my application's data. For financial applications storing transactional records, since concurrency is very important in that case, Amazon Elasticsearch Service is not very well suited for those cases. Traditional ways to store data like Oracle SQL Database used to handle this problem much better.
  • Centralized logging.
  • Handle tons of data.
  • Poor documentation.
  • Hard to debug issues.
Score 5 out of 10
Vetted Review
Verified User
Incentivized
AWS container is very fast, imagine previously I [spent] at least 30 minutes [setting] up one VM in my local server infrastructure [and] I [spent] around 150k to set up local server infrastructure with SAN, and [paid] a lot [for] electricity, internet, and firewall. But when I moved to ECS, I [found] it changed my work a lot. I deploy the server for developer and production use [in] only one minute. Fast provisioning vm and easy to scale my vm to bigger ram, cpu, hdd.
  • Stable, fast provisioning the VM, and also easy backup snapshot and restore.
  • Pay less than local server infrastructure, easy for collaboration work.
  • Really satisfied with this service from Amazon.
Previously we started using vmware, but it's very difficult [and] takes a lot of time to create one VM, but since we started using [Amazon Elasticsearch Service] it's great, fast, [and] it saves our IT [a lot of] time, especially for development.
  • Fast services and can scale very fast without affecting operation.
  • The cost is a bit expensive if compared with other clouds but [the] performance is very good.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Our team is using [Amazon] Elasticsearch to help us perform user lookups of data in our system. Instead of spending a lot of time and energy creating optimized queries in SQL Server, we were able to use Elasticsearch to quickly set up a system that searched through multiple data points and provide weighted results. One of the things we like the best is how easy it has been to set up the search, to do partial search matches for some data points, exact search matches for other data points, and then weight the results so that the best results are displayed first. This has allowed us to create a single "Google-like" search with minimal development effort.
  • Slice data by dates and times
  • Provide weighting of search results
  • Easy configuration and setup
  • Understanding how stale the data is and what data needs refreshed
Elasticsearch is a good alternative to relational databases for setting up complex searching of data. It's inbuilt features for slicing the data [in] different ways and its ability to add weights to search results makes it easy to set up complex searching scenarios. Given that data must be pushed to this service, it may be best suited for data that is not changing very rapidly.
  • Reducing time spent optimizing queries
  • Offloading resources around searching from our application
  • Elasticsearch has allowed us to spend more time on building features and less time on optimizing search queries
Score 8 out of 10
Vetted Review
Verified User
Incentivized
We use Elasticsearch to offer modern reporting to our users. They can quickly sort thru large datasets and see the information that matters to them.
  • Quick ingestion
  • Efficient data visualization thru Kibana
  • Managing production issues with shards is difficult
Amazon offers a simple to use and turnkey implementation of Elasticsearch. All the dev-ops side of implementing Elasticsearch is handled with a simple and intuitive UI. I would recommend Amazon Elasticsearch Service to others.
  • Ability to ingest large volume of data
  • Gave us the ability to produce some efficient reporting for our customers
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