Elastic Search has many pros, but the cons of it are that it is not structured, and we need to put all the things which are connected into a single index. Therefore, we cannot use it for our base structure database, but we always use it for supporting purposes. While part of Careem, there were hundreds of thousands of customers using the solution, and now that in a startup, the clients are no more than one hundred. Elastic Search requires maintenance. We need to keep it updated because Elastic Search normally launches new features and versions on both Kibana and Elastic Search sides. We need to keep updated ourselves, and also, we need to do maintenance on the storage side. Normally, we use Elastic Search for timelines, saving all the data from beginning to end, so normally the storage maintenance is an issue, and we have to increase the storage time to time, but it is not related to Elastic Search; it is actually related to our use case. There is lots of support for Elastic Search in different tools like Logstash which we normally use for integration, and there are other tools as well, but it is very easy and not a big issue for that. The Attack Discovery feature is not being used. Big businesses cannot survive without Elastic Search because it gives us very good visibility and handles our use cases very well. If we need something reliable and trustworthy as a solution, then Elastic Search is the way to go, as it is an integral part of big solutions. The overall review rating for Elastic Search is eight point five.
Hybrid observability was not used. Enterprise API, whether referring to ESB, API Gateway, or middleware, was not used. Serverless interaction with Kibana was not used. The overall rating for this review is 9 out of 10.
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.
Software Developer at a media company with 10,001+ employees
Real User
Top 20
Sep 26, 2025
I consider Elastic Search a very good project. On a scale of 1-10, I would give it a 10. The features and capabilities that Elastic Search provides are very easy to use, and the documentation is rich. You can find and understand everything here to use it properly. I would tell others looking into using Elastic Search that they can try it and see if it fits their use cases. Elastic Search is a very good product. I really appreciate all the features that it provides, and I hope this product continues its evolution in the way it has been.
Sr. Consultant at a computer software company with 51-200 employees
Consultant
Top 20
Aug 12, 2025
I have used Elastic Search, but I might not be aware of many internal details; I just used the API to create an index, manage data, and search. It's very useful. On a scale of 1-10, I rate it an eight.
If a feature for renaming indices could be added without affecting the performance of all other features, it would be nice to have. Overall, I rate Elasticsearch a ten out of ten.
Overall, considering key aspects like cost, learning curve, and data indexing architecture, Elasticsearch is a very good tool. I would rate it as a nine.
Information Security Engineer at a financial services firm with 11-50 employees
Real User
Top 20
Oct 15, 2024
For someone wanting to be a security analyst, Elasticsearch is a valuable tool. It helps organizations collect large amounts of logs from various platforms like Windows, Ubuntu, and Palo Alto Networks. I'd rate the solution eight out of ten.
I would rate it to others. Elasticsearch can be used for many things. It has a good indexing parameter and can be used for search patterns and more. If it's for observability, I would give it a nine out of ten. The only issue I have is with APM (Application Performance Monitoring). Elasticsearch as a product is different than Elasticsearch as a search engine. Elasticsearch is also different as an analytics tool. It depends on the analytical solution and how they want to fetch data from Elasticsearch as a database. As a search engine, it is one of the best. 90% of people use either Solar or Elasticsearch for web portals and other things. Nobody can challenge Elasticsearch in that area. So, out of ten, I would give it a ten. But for analytics, I'd give it an eight. It depends on my database and in-memory tools. If I use QlikView or other tools, I'll just use Elasticsearch as a database. It's just like any other database they are using for in-memory analytics. For observability, Elasticsearch, Logstash, and other things, it is a good component. It's good for tier-two enterprises. But when you define "enterprise," you must be specific. If you mean more than 2000 servers, then 90% of people won't consider it. There are other observability tools on the market. So, be specific in your query.
We are fully satisfied with the usage and support, rating it 8 out of 10. I recommend NGINX for managing traffic due to its multiple functionalities like load balancing, proxy management, and caching.
With the power of Kibana, we can easily and dynamically analyze and summarize our log data. The internet has information about all the technical solutions. I bought some courses from Udemy for Elastic Search. I also got some documents from Elastic Search. The documentation for Java is very good. It was sufficient to learn as a developer. I could integrate my products to Elastic Search easily. I use the default index for my solution, and it works very well. Elastic’s indexing policies are very good. I do not need any indexed operations for my solution. Overall, I rate the tool a nine out of ten.
Solutions Architect at a recruiting/HR firm with 1-10 employees
Real User
Top 10
Feb 8, 2024
By integrating Deepgram insights with the product, we've gained visibility into logging, service behavior, and cost optimization. I rate Elastic Search a nine out of ten.
My advice to anyone who is evaluating Elastic Search is to explore the user-friendly website and navigate to the documentation or resources section. Start with a basic overview of the components, and how they work together, and try simple tasks like searching or detecting. The key is to begin with something straightforward. Utilize the documentation to understand how to get started and explore the various integrations Elastic Search offers. Overall, I would rate it as an eight out of ten.
Logstash seems to have a very small capability to report errors, and that makes it difficult to troubleshoot. It would be nice to get some indication so as to save time.
We are a customer. I'm not sure which version we're using. I'm from the development team. The people who are doing the configuring work would know the version. I'd rate the solution seven out of ten. It is a good solution, yet not quite perfect.
Senior Product Manager at a tech services company with 501-1,000 employees
Real User
Nov 9, 2022
I would rate Elasticsearch as eight out of ten. Elasticsearch provides a lot of possibilities. You need to understand your requirements and how Elasticsearch can fulfill them. Somebody might be looking at a simple keyword service or attribute tagging. If you don't understand exactly what you're looking for, you'll get lost in their options and waste a lot of time.
Operations Manager at Cairo 3A for Agricultural and Animal Production
Real User
Oct 28, 2022
My advice to others is for them to make sure this solution satisfies their business needs because there are many solutions and providers, with a lot of options. There are solutions that have a lot of features that the business might not need and it is not good for the business to waste money on features not used. It was recommended by many peers not to seek many options in a solution that you are not going to use, and to concentrate on what is needed. I rate Elastic Enterprise Search a seven out of ten.
Senior Associate at a consultancy with 10,001+ employees
Real User
Oct 21, 2022
When using the solution, it is important to understanding indexing concepts and the proper way to search logs from a visualization point of view. These two items work together internally to produce logs that can be filtered to specifications. I rate the solution an eight out of ten.
General Manager at Andes Tecnología y Consultoría Ltda.
Real User
Sep 6, 2022
I rate this solution a seven out of ten. Because it is open-source, there is no technical support provided by the vendor, so we are moving to enterprise subscriptions for each of these products. We are allowed free licenses and implement enterprise or commercial licenses and the production of protections. An original criterion selects the software stack because they have to be good tools, but they all have to be open-source. Nobody considers it because the original team that started the project worked in an investigation organization and was closer to open-source software. They are not clear regarding the support of their solution when they go into production. That's why we are updating the licenses to interpret license subscriptions and assume their support for each software component.
Elastic Enterprise Search is a very good solution and they should keep doing good work. I'm a very satisfied customer because almost everything I need comes out of the book. You already have machine learning, alerts, the ability to search, APIs, inbuilt security, and integration to third-party authentication. I rate Elastic Enterprise Search a ten out of ten.
IT Secuirty Architect at a insurance company with 10,001+ employees
Real User
Nov 7, 2021
I would rate this solution 8 out of 10. I would recommend Elasticsearch if you don't have bigger budget limitations to use other enterprise solutions or if you want to avoid the vendor lock-in.
Senior Consultant at a tech services company with 10,001+ employees
Real User
Sep 15, 2021
I'm just a customer and an end-user. Our company is always using the latest updates. I'd advise new users that you need to do a POC or get a test installation. It's free of charge. It's important to ingest a lot of data so that you get a feeling of scalability and performance. To put something in your lab, for example, is very helpful. It's only when you have data in the system, that you can see the benefits of the Elastic environment. I would absolutely recommend the solution to others. I'd rate it at a nine out of ten. I've been pleased with its capabilities overall.
Technical Manager at a computer software company with 51-200 employees
Real User
Jul 8, 2021
I would tell potential users that they have to locate the data source and understand the data. They will have to decide on whether they have to go for a NoSQL or a relational database. If it's NoSQL, then what kind of data are you seeing? If it's more textual data, then you're going to read more. So, I would recommend Elasticsearch. Otherwise, you have other databases like MongoDB and Cassandra. On a scale from one to ten, I would give ELK Elasticsearch a seven.
Senior Analyst at a tech services company with 10,001+ employees
Real User
May 20, 2021
I would advise others to first know Linux because it would most probably be on Linux. If you're good at Linux, you will be good at this as well. I would rate ELK Elasticsearch an eight out of ten.
The most important thing to keep in mind is that it is not as they advertise on their site. If you want to scale up and are looking for a big deployment, you must read everything. You also need support from the company itself. I would rate ELK Elasticsearch a seven out of ten.
I like this solution, but it has too much hands-on time required tweaking to get it up and running. I have no plans to continue using this product. Currently, I am focused on SIEMonster because I signed a partnership and I would like to sell a total product. It doesn't make sense to spread across multiple products. I would like to earn money out of it, so I'm focusing currently on SIEMonster. I think that Elasticsearch is a good product and cheaper than Splunk. When I check Gartner, I don't see mention of Elasticsearch, it seems they need to make some improvements. I would rate this solution a seven out of ten.
The solution has a lot of features. They have machine learning jobs they can implement, I'm not there yet, but I can use anomaly detection to see there are various processes that can find users that aren't supposed to log onto certain machines. All of these features are visual and graphical. I can show it as a bar chart, a pie chart, I can Instagram, or I can split chart. The power to see everything on the front end is so much more powerful. I rate ELK Elasticsearch a ten out of ten.
System Administrator and DevOps Engineer at a tech services company with 10,001+ employees
Real User
Nov 23, 2020
For anyone looking to implement a monitoring product with almost no cost or at a cheaper price, I would suggest the ELK stack. However, it does require a high skill set because of the difficulty with implementation. I would rate this solution a six out of 10.
Chief Data Scientist at Everlytics Data Science Pte Ltd
Real User
Nov 19, 2020
You can spin up Elastic ELK Elasticsearch fully-managed service either on AWS, GCP, or Azure, or have your own on-premises installation and dockerize it. Whereas the AWS Elasticsearch is available only on AWS. That's the hosting difference. Elastic ELK Elasticsearch comes with a support-only subscription, and there are a lot of updates happening. Kibana is constantly improved and there’s a new release every two weeks.
Head of Technology Operations at a financial services firm with 11-50 employees
Real User
Oct 22, 2020
For anyone who is looking into implementing this solution, the only tip is to get your models for the type of actual use that you are looking at upfront in order to have a good run. I would rate ELK Elasticsearch a seven out of ten.
Associate Software Engineer at a tech services company with 51-200 employees
Real User
Oct 11, 2020
I also use Kibana, which is integrated with Elasticsearch. Kibana is for visualization and we can also customize Elasticsearch using Kibana. In summary, Elasticsearch is a very useful product that I can quickly recommend. I would rate this solution an eight out of ten.
Lead Software Architect at a tech services company with 51-200 employees
Real User
Aug 2, 2020
We have some devices that are managed by AWS and we have our own information with switches that are self-hosted. ELK Elasticsearch is a product that I recommend. I would rate this solution a seven out of ten.
I'm just using it as a customer We tend to use the latest versions of the solution. We try to upgrade it on a regular basis. I'd advise other companies considering implementing the solution to get a team in that knows the product and try to take advantage of their knowledge. It will help reduce the pain of the learning curve. I'd rate the solution eight out of ten. I would not give it a ten because of the steep learning curve. I know what the product is, but many do not, and for them it will be quite difficult to get started without becoming very frustrated in the process.
Cyber Security Professional at Defensive Cyber Security Center Germany
Real User
May 10, 2020
For anyone considering implementing this solution, I would say take a good hard look at your own infrastructure resources and scalability as you have to future proof everything. Whether it's scale or increase in customers building up through your actual hardware and your network infrastructure. You need to know it's capable of performing the tasks needed, because sometimes you outgrow yourself. So, I would say look at your resources and how it can be scaled. I would rate this solution a nine out of 10.
Manager at a tech services company with 11-50 employees
Real User
Dec 15, 2019
The advice I would give to others considering this solution is that you have to have someone knowledgeable managing the system. You have to know the needs, know how to manage queries, and understand the visualization. You have to have someone working on it and dedicated to it so that you can manage it. It is not just plug-and-play. If you decide to run with it, the performance and the result can be very satisfactory. We did not have any issues with achieving what we tried to do. When we need certain data, we always find it. On a scale from one to ten where one is the worst and ten is the best, I would rate ELK Elasticsearch as an eight out of ten. What would make it a ten for us is something I wouldn't know at this point. Until we use it more heavily in production then we'll see how it performs under a full load and we'll have a better idea of what needs to be improved.
Data Scientist at a tech vendor with 51-200 employees
Real User
Dec 9, 2019
You can test the product for your use case on their user free trial, they offer a seven or 14-day free trial, You can put it up on cloud and just push your data to check if your use cases are being handled or not. It's a quick test of the waters. I would rate this product an eight out of 10.
My advice for anybody considering this solution is that it is an easy to use tool, but for work that is not complex. If on the other hand, the work is more complex, with more data and perhaps a clustering environment, then they may have to consider something more stable and more robust. I would rate this solution a seven out of ten.
In general, we have many advantages from the features of Elasticsearch, but there are questions mostly about money, not about technical features, that are of concern. I would rate Elasticsearch eight/nine out of ten. We have enough possibilities and features with Elasticsearch for our business requirements.
Elasticsearch is a prominent open-source search and analytics engine known for its scalability, reliability, and straightforward management. It's a favored choice among enterprises for real-time data search, analysis, and visualization. Open-source Elasticsearch is free, offering a comprehensive feature set and scalability. It allows full control over deployments but requires managing and maintaining the infrastructure. On the other hand, Elastic Cloud provides a managed service with features...
Elastic Search has many pros, but the cons of it are that it is not structured, and we need to put all the things which are connected into a single index. Therefore, we cannot use it for our base structure database, but we always use it for supporting purposes. While part of Careem, there were hundreds of thousands of customers using the solution, and now that in a startup, the clients are no more than one hundred. Elastic Search requires maintenance. We need to keep it updated because Elastic Search normally launches new features and versions on both Kibana and Elastic Search sides. We need to keep updated ourselves, and also, we need to do maintenance on the storage side. Normally, we use Elastic Search for timelines, saving all the data from beginning to end, so normally the storage maintenance is an issue, and we have to increase the storage time to time, but it is not related to Elastic Search; it is actually related to our use case. There is lots of support for Elastic Search in different tools like Logstash which we normally use for integration, and there are other tools as well, but it is very easy and not a big issue for that. The Attack Discovery feature is not being used. Big businesses cannot survive without Elastic Search because it gives us very good visibility and handles our use cases very well. If we need something reliable and trustworthy as a solution, then Elastic Search is the way to go, as it is an integral part of big solutions. The overall review rating for Elastic Search is eight point five.
Hybrid observability was not used. Enterprise API, whether referring to ESB, API Gateway, or middleware, was not used. Serverless interaction with Kibana was not used. The overall rating for this review is 9 out of 10.
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.
I consider Elastic Search a very good project. On a scale of 1-10, I would give it a 10. The features and capabilities that Elastic Search provides are very easy to use, and the documentation is rich. You can find and understand everything here to use it properly. I would tell others looking into using Elastic Search that they can try it and see if it fits their use cases. Elastic Search is a very good product. I really appreciate all the features that it provides, and I hope this product continues its evolution in the way it has been.
I have used Elastic Search, but I might not be aware of many internal details; I just used the API to create an index, manage data, and search. It's very useful. On a scale of 1-10, I rate it an eight.
If a feature for renaming indices could be added without affecting the performance of all other features, it would be nice to have. Overall, I rate Elasticsearch a ten out of ten.
Overall, considering key aspects like cost, learning curve, and data indexing architecture, Elasticsearch is a very good tool. I would rate it as a nine.
I would rate Elasticsearch at eight out of ten.
I rate Elastic Search nine out of ten.
For someone wanting to be a security analyst, Elasticsearch is a valuable tool. It helps organizations collect large amounts of logs from various platforms like Windows, Ubuntu, and Palo Alto Networks. I'd rate the solution eight out of ten.
Overall, I would rate it a nine out of ten. I would definitely recommend it to other users.
I would rate it to others. Elasticsearch can be used for many things. It has a good indexing parameter and can be used for search patterns and more. If it's for observability, I would give it a nine out of ten. The only issue I have is with APM (Application Performance Monitoring). Elasticsearch as a product is different than Elasticsearch as a search engine. Elasticsearch is also different as an analytics tool. It depends on the analytical solution and how they want to fetch data from Elasticsearch as a database. As a search engine, it is one of the best. 90% of people use either Solar or Elasticsearch for web portals and other things. Nobody can challenge Elasticsearch in that area. So, out of ten, I would give it a ten. But for analytics, I'd give it an eight. It depends on my database and in-memory tools. If I use QlikView or other tools, I'll just use Elasticsearch as a database. It's just like any other database they are using for in-memory analytics. For observability, Elasticsearch, Logstash, and other things, it is a good component. It's good for tier-two enterprises. But when you define "enterprise," you must be specific. If you mean more than 2000 servers, then 90% of people won't consider it. There are other observability tools on the market. So, be specific in your query.
We are fully satisfied with the usage and support, rating it 8 out of 10. I recommend NGINX for managing traffic due to its multiple functionalities like load balancing, proxy management, and caching.
With the power of Kibana, we can easily and dynamically analyze and summarize our log data. The internet has information about all the technical solutions. I bought some courses from Udemy for Elastic Search. I also got some documents from Elastic Search. The documentation for Java is very good. It was sufficient to learn as a developer. I could integrate my products to Elastic Search easily. I use the default index for my solution, and it works very well. Elastic’s indexing policies are very good. I do not need any indexed operations for my solution. Overall, I rate the tool a nine out of ten.
By integrating Deepgram insights with the product, we've gained visibility into logging, service behavior, and cost optimization. I rate Elastic Search a nine out of ten.
The solution suits medium to large companies better. I rate it a nine out of ten.
My advice to anyone who is evaluating Elastic Search is to explore the user-friendly website and navigate to the documentation or resources section. Start with a basic overview of the components, and how they work together, and try simple tasks like searching or detecting. The key is to begin with something straightforward. Utilize the documentation to understand how to get started and explore the various integrations Elastic Search offers. Overall, I would rate it as an eight out of ten.
Overall, I would rate the solution a seven out of ten. The free version is not very useful.
I would rate the product a nine out of ten.
I would rate the product a nine out of ten.
Logstash seems to have a very small capability to report errors, and that makes it difficult to troubleshoot. It would be nice to get some indication so as to save time.
I would recommend the solution to others. I'd rate the solution nine out of ten.
We are a customer. I'm not sure which version we're using. I'm from the development team. The people who are doing the configuring work would know the version. I'd rate the solution seven out of ten. It is a good solution, yet not quite perfect.
I would rate Elasticsearch as eight out of ten. Elasticsearch provides a lot of possibilities. You need to understand your requirements and how Elasticsearch can fulfill them. Somebody might be looking at a simple keyword service or attribute tagging. If you don't understand exactly what you're looking for, you'll get lost in their options and waste a lot of time.
My advice to others is for them to make sure this solution satisfies their business needs because there are many solutions and providers, with a lot of options. There are solutions that have a lot of features that the business might not need and it is not good for the business to waste money on features not used. It was recommended by many peers not to seek many options in a solution that you are not going to use, and to concentrate on what is needed. I rate Elastic Enterprise Search a seven out of ten.
When using the solution, it is important to understanding indexing concepts and the proper way to search logs from a visualization point of view. These two items work together internally to produce logs that can be filtered to specifications. I rate the solution an eight out of ten.
I rate this solution a seven out of ten. Because it is open-source, there is no technical support provided by the vendor, so we are moving to enterprise subscriptions for each of these products. We are allowed free licenses and implement enterprise or commercial licenses and the production of protections. An original criterion selects the software stack because they have to be good tools, but they all have to be open-source. Nobody considers it because the original team that started the project worked in an investigation organization and was closer to open-source software. They are not clear regarding the support of their solution when they go into production. That's why we are updating the licenses to interpret license subscriptions and assume their support for each software component.
I'd rate the solution nine out of ten. I'm a customer and end-user.
Elastic Enterprise Search is an open-source solution. I rate Elastic Enterprise Search a ten out of ten.
I rate Elastic Enterprise Search a nine out of ten.
Elastic Enterprise Search is a very good solution and they should keep doing good work. I'm a very satisfied customer because almost everything I need comes out of the book. You already have machine learning, alerts, the ability to search, APIs, inbuilt security, and integration to third-party authentication. I rate Elastic Enterprise Search a ten out of ten.
It is a good choice, but you have to take your time to learn it. Its learning curve can be hard. I would rate it an eight out of 10.
I would rate this solution 8 out of 10. I would recommend Elasticsearch if you don't have bigger budget limitations to use other enterprise solutions or if you want to avoid the vendor lock-in.
The distributed installation is the way to go. I would rate ELK Elasticsearch a nine out of ten.
I'm just a customer and an end-user. Our company is always using the latest updates. I'd advise new users that you need to do a POC or get a test installation. It's free of charge. It's important to ingest a lot of data so that you get a feeling of scalability and performance. To put something in your lab, for example, is very helpful. It's only when you have data in the system, that you can see the benefits of the Elastic environment. I would absolutely recommend the solution to others. I'd rate it at a nine out of ten. I've been pleased with its capabilities overall.
I would tell potential users that they have to locate the data source and understand the data. They will have to decide on whether they have to go for a NoSQL or a relational database. If it's NoSQL, then what kind of data are you seeing? If it's more textual data, then you're going to read more. So, I would recommend Elasticsearch. Otherwise, you have other databases like MongoDB and Cassandra. On a scale from one to ten, I would give ELK Elasticsearch a seven.
I would advise others to first know Linux because it would most probably be on Linux. If you're good at Linux, you will be good at this as well. I would rate ELK Elasticsearch an eight out of ten.
The most important thing to keep in mind is that it is not as they advertise on their site. If you want to scale up and are looking for a big deployment, you must read everything. You also need support from the company itself. I would rate ELK Elasticsearch a seven out of ten.
I like this solution, but it has too much hands-on time required tweaking to get it up and running. I have no plans to continue using this product. Currently, I am focused on SIEMonster because I signed a partnership and I would like to sell a total product. It doesn't make sense to spread across multiple products. I would like to earn money out of it, so I'm focusing currently on SIEMonster. I think that Elasticsearch is a good product and cheaper than Splunk. When I check Gartner, I don't see mention of Elasticsearch, it seems they need to make some improvements. I would rate this solution a seven out of ten.
The solution has a lot of features. They have machine learning jobs they can implement, I'm not there yet, but I can use anomaly detection to see there are various processes that can find users that aren't supposed to log onto certain machines. All of these features are visual and graphical. I can show it as a bar chart, a pie chart, I can Instagram, or I can split chart. The power to see everything on the front end is so much more powerful. I rate ELK Elasticsearch a ten out of ten.
For anyone looking to implement a monitoring product with almost no cost or at a cheaper price, I would suggest the ELK stack. However, it does require a high skill set because of the difficulty with implementation. I would rate this solution a six out of 10.
You can spin up Elastic ELK Elasticsearch fully-managed service either on AWS, GCP, or Azure, or have your own on-premises installation and dockerize it. Whereas the AWS Elasticsearch is available only on AWS. That's the hosting difference. Elastic ELK Elasticsearch comes with a support-only subscription, and there are a lot of updates happening. Kibana is constantly improved and there’s a new release every two weeks.
For anyone who is looking into implementing this solution, the only tip is to get your models for the type of actual use that you are looking at upfront in order to have a good run. I would rate ELK Elasticsearch a seven out of ten.
I also use Kibana, which is integrated with Elasticsearch. Kibana is for visualization and we can also customize Elasticsearch using Kibana. In summary, Elasticsearch is a very useful product that I can quickly recommend. I would rate this solution an eight out of ten.
We have some devices that are managed by AWS and we have our own information with switches that are self-hosted. ELK Elasticsearch is a product that I recommend. I would rate this solution a seven out of ten.
I'm just using it as a customer We tend to use the latest versions of the solution. We try to upgrade it on a regular basis. I'd advise other companies considering implementing the solution to get a team in that knows the product and try to take advantage of their knowledge. It will help reduce the pain of the learning curve. I'd rate the solution eight out of ten. I would not give it a ten because of the steep learning curve. I know what the product is, but many do not, and for them it will be quite difficult to get started without becoming very frustrated in the process.
For anyone considering implementing this solution, I would say take a good hard look at your own infrastructure resources and scalability as you have to future proof everything. Whether it's scale or increase in customers building up through your actual hardware and your network infrastructure. You need to know it's capable of performing the tasks needed, because sometimes you outgrow yourself. So, I would say look at your resources and how it can be scaled. I would rate this solution a nine out of 10.
The advice I would give to others considering this solution is that you have to have someone knowledgeable managing the system. You have to know the needs, know how to manage queries, and understand the visualization. You have to have someone working on it and dedicated to it so that you can manage it. It is not just plug-and-play. If you decide to run with it, the performance and the result can be very satisfactory. We did not have any issues with achieving what we tried to do. When we need certain data, we always find it. On a scale from one to ten where one is the worst and ten is the best, I would rate ELK Elasticsearch as an eight out of ten. What would make it a ten for us is something I wouldn't know at this point. Until we use it more heavily in production then we'll see how it performs under a full load and we'll have a better idea of what needs to be improved.
You can test the product for your use case on their user free trial, they offer a seven or 14-day free trial, You can put it up on cloud and just push your data to check if your use cases are being handled or not. It's a quick test of the waters. I would rate this product an eight out of 10.
This solution is ok for me and my business. I would rate this solution an eight out of ten.
My advice for anybody considering this solution is that it is an easy to use tool, but for work that is not complex. If on the other hand, the work is more complex, with more data and perhaps a clustering environment, then they may have to consider something more stable and more robust. I would rate this solution a seven out of ten.
In general, we have many advantages from the features of Elasticsearch, but there are questions mostly about money, not about technical features, that are of concern. I would rate Elasticsearch eight/nine out of ten. We have enough possibilities and features with Elasticsearch for our business requirements.