The main use cases for Elastic Search are index building and retrieving information using Elastic Search vector, vector search, and related functionalities. Search is the primary use case.
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Boosted search efficiency through real-time querying and seamless indexing for high-volume product data
What is our primary use case?
What is most valuable?
Computation is very good. The scalability is very good because we have a huge customer database that is searching lots of products, and auto-scaling or load balancing are the prominent features we are using in this.
If we look at the impact on operational efficiency, we can see that decision-making has become much faster due to real-time data and quick responses. We have also implemented many automations, which enhance our processes. For example, when we optimize certain fields to improve search functionality, it yields great results.
What needs improvement?
I have not explored Elastic Search at the most. Searching from vector DB is available in Elastic Search, and there is one more concept of graph searching or graph database searching. I have not explored it, but if it is not there, that would be an improvement area where Elastic Search can improve.
For how long have I used the solution?
I have been working with Elastic Search for more than two years.
What do I think about the stability of the solution?
It is very reliable, and it has no downtime.
What do I think about the scalability of the solution?
I believe it is scalable. Every day, we have thousands of users continuously utilizing the search feature. We haven't encountered any problems so far, and there is the potential for auto-scaling. It is currently a scalable solution.
How are customer service and support?
We have not contacted them yet. So far, we haven't had any need.
How would you rate customer service and support?
Positive
How was the initial setup?
The initial setup is straightforward.
What about the implementation team?
We have a team of developers, so it is internally managed.
What was our ROI?
We have not calculated the ROI for Elastic Search, but we are a consumer platform where numerous searches are happening, and we are getting very good results from the current infrastructure of Elastic Search. Though the exact numbers or ROI were never calculated, the performance has been beneficial.
What's my experience with pricing, setup cost, and licensing?
It is average compared to other platforms. There isn’t anything particularly special about the pricing. However, the pay-as-you-go model is advantageous for the organization, as we only pay for what we utilize.
What other advice do I have?
We are using AWS for our solutions. In AWS, we are heavily using Redshift and Glue. We focus more on vector searches and boosting the keywords, and all those features we are using heavily. In search, the key parameter that we boost up during indexing is essential.
We self-implement Elastic Search in our e-commerce application. We are not currently doing a regex setup for RAG Playground, but there is a plan to do that. We are more into vector searches when it comes to how effectively the hybrid search capability meets our needs for combining traditional keyword and vector searches.
Regarding the workflow, we are using the API for real-time inference because lots of data is being loaded at real-time on the application, and it is working well for us.
I can definitely recommend Elastic Search to be used wherever you have consumer search capabilities needed in a large or scalable manner because it is very effective.
I would rate Elastic Search an eight out of ten.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)
Elasticsearch provides best searching and data aggregation capabilities
What do you like best about the product?
I used Elasticsearch to store salary statistical data and to perform mathematical operations on that data. What I appreciated most about Elasticsearch is that its queries offer built-in support for operations such as calculating the mean, average, and percentiles.
What do you dislike about the product?
The documentation for Elasticsearch could use some improvement. It would be helpful if more detailed information were included.
What problems is the product solving and how is that benefiting you?
Elasticsearch offers outstanding text search capabilities with minimal latency. Along with simple text search, it also provides capabilities like string matching, wildcards, fuzzy logic etc
Powerful and Flexible
What do you like best about the product?
The flexibility to solve many problems, the expansive feature set allows us to use Elasticsearch in a variety of ways.
What do you dislike about the product?
Slight learning curve, as it can do many things, you need to be aware of the use case you are solving for or it can get overwhelming without proper planning.
What problems is the product solving and how is that benefiting you?
Helping us with enterprise search functions on several of our internal and external facing applications
Good product, meets our needs
What do you like best about the product?
Able to consume and collect our data without any surprise costs.
What do you dislike about the product?
Support can take a while to get back with you, and the product is dependent on a lot of other products such as zookeeper that have different timelines and support models.
What problems is the product solving and how is that benefiting you?
Elastic is used to collect, catalog and score security data within the Agency. It provides a useful dashboard that allows access to all underlying data.
Elasticsearch for Search and Match
What do you like best about the product?
Combining traditional keyword search (BM25) with semantic vector search, enabling powerful hybrid retrieval. This makes it ideal for modern search experiences that require both precision and contextual understanding
What do you dislike about the product?
Complex Configuration
The configuration process—especially for Elastic Enterprise Search—is often described as difficult and time-consuming. Users find that even basic setup tasks can be challenging without deep technical kno
The configuration process—especially for Elastic Enterprise Search—is often described as difficult and time-consuming. Users find that even basic setup tasks can be challenging without deep technical kno
What problems is the product solving and how is that benefiting you?
Search and Match
Search logs in real time
Visualize system health
Detect anomalies and performance bottlenecks
Search logs in real time
Visualize system health
Detect anomalies and performance bottlenecks
Scalable search, log analytics and data exploration
What do you like best about the product?
1.Performance and scalability
2. Advanced search capabilities
3.Analytics Integration
4. APIs & ecosystem
5. Security
2. Advanced search capabilities
3.Analytics Integration
4. APIs & ecosystem
5. Security
What do you dislike about the product?
1. Resource intensive
2. Complexity
3. Licensing changes
2. Complexity
3. Licensing changes
What problems is the product solving and how is that benefiting you?
Elastic provides advanced search capabilities helping us do full-text searches, fuzzy matching, aggregations in a quick performance oriented way.
Scalable and Robust, working with on-prem ECE
What do you like best about the product?
This platform is impressively fast, even when handling petabytes of data in queries. It scales smoothly without any issues and is straightforward to manage. The availability of both a GUI and an API adds to its flexibility. Cluster management and monitoring are made very simple with this solution.
What do you dislike about the product?
Troubleshooting can be frustrating at times, and occasionally it takes a while to receive a response from support.
What problems is the product solving and how is that benefiting you?
Storing technical and audit logging for a big organisation, this has all to do with compliance.
Elastic search product is easy to manage
What do you like best about the product?
Elastic search has good indexing and search capabilities
What do you dislike about the product?
Elastic search should allow trial version with sample indexes
What problems is the product solving and how is that benefiting you?
Elastic search upgrade was smooth.
Simplified agent deployment and highly responsive support
What is our primary use case?
My main use case is for security, specifically for the SIEM aspect, as I work as a cybersecurity engineer.
We specifically use this system for security-related topics. We have a dedicated environment for Large Language Models (LLMs). We have connected our LLM, but our primary focus remains on security. When we encounter any incidents or need to gather information about connected IPs, we rely on established rules and alerts. We utilize the chat functionality of this LLM to generate queries in Kibana language.
What is most valuable?
My favorite feature is the ease of use, particularly in how you integrate the agent. I've been using it since version 7, and we're on version 9 now, and I've seen the progress from using Beats to using the agent, making it so simple today to enroll a server with the Elastic Agent.
What needs improvement?
Deploying the Elastic Agent internally is relatively straightforward; it only requires a few commands to be run on the server. However, to manage this deployment at scale, we needed to develop a solution using Ansible. This involved creating scripts to install, restart, and uninstall the agent. While I would have preferred if Elastic had provided an official solution for these tasks, they haven't yet developed one that addresses all the necessary aspects. As a result, we've taken it upon ourselves to create these tools internally.
There are two areas in which it could improve. One is the smoother enrollment process for 1,000 or 2,000 servers at the same time, rather than having to develop something internal.
The second topic is the actual support of YARA rules—it's Y-A-R-A, which is specific for security. As of today, this is not supported, and I've been asking for a while now; I'm unsure if they will ever release it.
For how long have I used the solution?
I have been using this solution for at least four years.
What do I think about the stability of the solution?
I haven't seen any downtime.
What do I think about the scalability of the solution?
It is really scalable. Since we're on the cloud, whenever we need to upgrade or add resources, they handle everything. It takes a couple of hours due to the amount of data we have, and I've never faced any issues during upgrades.
How are customer service and support?
I have contacted technical support because we encountered issues when we started using the Elastic integrations, some of which were not finalized on their side. I had countless meetings with engineers from Elastic, including product managers and support engineers, to work on and fix the integrations we wanted to use. They have always been really responsible and responsive to my requests. Once, we had an issue with GCP, Google Cloud Platform, and they even sent us a complimentary five or six hours with an Elastic consultant to help set things up.
I would give them a nine out of ten because they are very responsive. They clearly know what they are talking about. I never encountered a situation where the support team didn’t understand what we needed.
How would you rate customer service and support?
Positive
How was the initial setup?
The initial setup process took around a month.
What they need is to be more transparent about the actual setup of the cluster and the deployment process. When using Elastic out of the box, there is information that is not readily available, requiring users to dig deep into the documentation to truly understand how it works. If you're looking to set up the cluster automatically, it works well for testing purposes. However, when installing two thousand servers at once, if your deployment isn't large enough, it can lead to crashes. Occasionally, we have to delete the logs just to access the interface. Therefore, I believe they should provide clearer guidance on using the deployment manager effectively.
We started four years ago with 200-300 servers, and now we are at around 2,000 servers. The learning curve involved understanding how it works, doing labs, and the difference between Elastic Search and competitors. Elastic really helped with support; we had weekly sessions with engineers from their side to assist us in setting up.
Maintenance on my end is limited to updates. Since we are using Elastic Cloud, they take care of the infrastructure.
What's my experience with pricing, setup cost, and licensing?
I am familiar with the pricing, as we negotiated it last year. Compared to other tools, it's fair. However, if we are talking with full transparency, Elastic pushes clients to buy the Enterprise edition instead of the Premium edition, and we don't see the value in that other than to spend more money more quickly. So, while pricing is good and what we expect to pay for this type of product, I'd love to finalize this concern.
Which other solutions did I evaluate?
We've tested multiple open-source tools based on Elastic before signing with them, including one tool called Wazuh that is built on top of Elastic. We've also tested the open-source edition of Elasticsearch where we manage the cluster and Splunk. Overall, I believe Elastic Cloud is still one of the best products out there.
What other advice do I have?
I would rate this solution an eight out of ten.
Has improved team efficiency through faster data access and customizable monitoring dashboards
What is our primary use case?
We use Elastic Cloud (Elasticsearch Service), Kibana, Enterprise Search, and on-premise as in a cloud environment within our Bosch environment, and we have different customers using the search, ML, and other services.
One of our customers uses Elastic Cloud (Elasticsearch Service) Agents out of the box when their server is installed, and this captures the metrics from the different servers within their environment, giving a unified Kibana view in the form of dashboards and helping us to understand the different key metrics which are relevant for them. They also use Elastic Cloud (Elasticsearch Service) for their search and indexing operations, and they also use agents and Fleet as different integration options, and finally, they also use the MLOps for their Elastic Cloud (Elasticsearch Service) ML for their AIOps purposes.
We've got close to about 50-plus customers and we've got three huge clusters of Elastic Cloud (Elasticsearch Service) on three different environments, and customers are happy.
What is most valuable?
One of the best features that Elastic Cloud (Elasticsearch Service) offers is their wonderful documentation as the technical support is very helpful. Every time I have a doubt, it's very easy to go through the Elastic articles, and if I have any questions and raise a support case, the technical support team provides valuable insights and recommendations. Even if I'm not aware of them, it really helps to make the product experience much better.
The integrations and features of Elastic Cloud (Elasticsearch Service) are very much kept up to date, and there's at least one or more use cases suiting every single need. There's also good room for customization, as Elastic Cloud (Elasticsearch Service) understands that different customers can have different needs, allowing customers to add their own integrations and edit or update them as they wish.
There have been quite a lot of good outcomes since using Elastic Cloud (Elasticsearch Service); customers have been able to use their data much faster and more effectively, and it definitely stands as one of the best observability platforms. We are also looking at integrating Elastic Cloud (Elasticsearch Service) along with certain other observability tools and CI/CD tools to give an overall comprehensive experience to our customers.
Elastic Cloud (Elasticsearch Service) is highly scalable, giving great options to scale the solution for the customer as at the cluster level. I've seen customers being able to deliver their results or web pages to their end users in a much faster way, increasing overall productivity and usage of their respective products, therefore leading to more profits. Using other conventional methods have been costly, so Elastic Cloud (Elasticsearch Service) has been a very cost-effective solution, and most importantly, the scalability meaning that you can upscale or downscale or even auto-scale the solutions as per the need has really reduced unnecessary waste, helping in cost reduction.
What needs improvement?
I don't think Elastic Cloud (Elasticsearch Service) has any sort of disadvantages per se; most of the features are pretty good and up to date.
We have some cost-effective indexing as searches with Elastic Cloud (Elasticsearch Service), and there could be other ways where we can probably improve in terms of the design of documentation. Sometimes it gets tricky to navigate through the user manuals because there are different forms of links. For example, we are speaking about ECE 3.x and ECE 4.x, and there are different sets of documentation for 3.x and 4.x. Sometimes it gets tricky to navigate through the documents, and the links can be difficult to catch upon. The content is fantastic, but if there is a better way to navigate through the documentation, that would be really great.
Mostly it's related to some sort of sloppy documentation at times, and we also have operational complexity. For example, we have some cases where the resource consumption due to the JVM could be pretty high; these are design-level issues and have also been discussed in technical topics, and if these could be improved, overall, that would be great.
For how long have I used the solution?
I have been using Elastic Cloud (Elasticsearch Service) for close to about five to six years.
What do I think about the stability of the solution?
Mostly Elastic Cloud (Elasticsearch Service) has been stable.
What do I think about the scalability of the solution?
Elastic Cloud (Elasticsearch Service) is highly scalable, giving great options to scale the solution for the customer as at the cluster level.
How are customer service and support?
Customer support for Elastic Cloud (Elasticsearch Service) is great, as I have mentioned in the past; they provide great technical support, and the support articles are great, and the technical team is really brilliant and smart.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
Previously, we used Splunk and that's not really effective; it is effective in its own way, but Elastic Cloud (Elasticsearch Service) is more of an integrated solution that has a lot of benefits and provides more features than Splunk does.
How was the initial setup?
One time I was stuck in a technical issue with upgrading our Elastic Cloud (Elasticsearch Service) cluster operator, and it actually happened to be a completely different issue. I was probably misguided thinking that the root cause could have been something else, so Elastic Cloud (Elasticsearch Service) support helped me to deep dive into the case. We've had a couple of calls together, a lot of diagnostics were reviewed, and eventually, we were set on the right path realizing that there could be something else actually wrong and not what I had in mind, and then they set me in the right direction providing the steps to properly fix that; I was quite impressed by the way they and their team handled it.
What was our ROI?
A lot of money and time have definitely been saved with Elastic Cloud (Elasticsearch Service); I do not have the exact metrics, but overall, we've had pretty good results and outcomes.
Which other solutions did I evaluate?
We also went through some open-source alternatives OpenSearch, Solr, as DataDog before choosing Elastic Cloud (Elasticsearch Service). We still use a few of the other solutions for different use cases, but predominantly, Elastic Cloud (Elasticsearch Service) has been the main use of our solution.
What other advice do I have?
I've covered pretty much everything regarding Elastic Cloud (Elasticsearch Service) in our previous questions.
It's a great product; it has so many features, great customer support, and it definitely has all rights to fit into every single use case of your applications.
On a scale of one to ten, I would give Elastic Cloud (Elasticsearch Service) a rating of nine.
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