Elastic Search Reviews

The tool's stability and performance are good. 

Elastic Search needs to improve its technical support. It should be customer-friendly and have good support. 

I have been using the product for a year. 

The tool is stable; I rate it an eight to nine out of ten. 

The product is scalable, and I rate it a ten out of ten. My company has three users. We use it regularly. 

You need three resources to handle the deployment. 

The tool is not expensive. Its licensing costs are yearly. 

I rate Elastic Search an eight out of ten. You can use the product if you are looking for value for money. 

We use the product for log analytics and metrics features. 

We can easily collect all the data and view historical trends using the product. We can view the applications and identify the issues effectively.

They could improve some of the platform's infrastructure management capabilities. There should be better visualization and insights about the cost of the SaaS services, which are not effective. Additionally, there needs to be more native integrations to merge the data.

We have been using Elastic Search for about a year.

I rate the stability a ten out of ten.

It is a highly scalable application. We have 15 users in our management team. I rate the scalability an eight out of ten.

I have experience working with Splunk in the past.

The initial setup for the SaaS platform is quite easy. We took assistance from an engineer for the onboarding. Thus, it was straightforward for us. However, there could be a better integration with AWS.

I rate the process a seven out of ten.

I rate Elastic Search's pricing an eight 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.

We use the solution for search engines and indexing. 

The solution is valuable for log analytics. 

The solution's integration and configuration are not easy. Not many people know exactly what to do.  

I have been working with the product for five years. 

The product's deployment took a couple of days to complete. 

The product's deployment was done in-house by myself. 

I would rate the product a nine out of ten. 

We are internal integrators. We are in the bigger group as of now, but other groups, our clients, are affiliates from our group. They are our internal clients. 

The solution is currently on-premises.

I was mostly responsible for the SOC team, and I helped them create the detection rules for the production. I wanted to know how it could be implemented in different kinds of products, like Sentinel.

The most valuable features are the detection and correlation features.

Something that could be improved is better integrations with Cortex and QRadar, for example. 

I have been using this solution for no more than one year. 

Not really, because I'm not the engineer and so most problems appear during the installations or maintenance and I'm not in developing infrastructure operations.

The price of Elasticsearch is fair. It is a more expensive solution, like QRadar. The price for Elasticsearch is not much more than other solutions we have.

I would say that Elasticsearch is better than all the other solutions. QRadar is getting better, but it is still behind Elasticsearch in my opinion.

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.

We are using ELK Elasticsearch in a database. We use both Logstash and Kibana. Kibana is used for monitoring where the data is coming from.

The solution has good security features. I have been happy with the dashboards and interface.

There are some features lacking in ELK Elasticsearch.

I have been using ELK Elasticsearch for approximately two years.

We had some stability issues where we could not access the application.

We have approximately five people in my organization using ELK Elasticsearch.

All the installations were directly set up on the local servers.

The solution is free.

Elasticsearch is open source.

I rate ELK Elasticsearch an eight out of ten.

We use ELK Elasticsearch for storing application data logs.

Elasticsearch includes a graphical user interface (GUI) called Kibana. The GUI features are extremely beneficial to us.

Elasticsearch includes mechanisms for ingesting data into the cluster. So it would be great if those mechanisms could be simplified.

Improving machine learning capabilities would be beneficial.

I have been working with ELK Elasticsearch for four years.

We are using the latest version.

We have no issues with the stability of ELK Elasticsearch, it's quite reliable.

ELK Elasticsearch is a scalable product

This solution is used by five to ten people in our organization.

ELK Elasticsearch is used on a daily basis.

We have not contacted technical support.

We had a couple of issues that we were able to resolve by looking up the public information that is available on the internet.

There is a lot of community support for this solution.

The initial setup was straightforward and quite simple.

The installation took between six and eight hours to complete.

There is no maintenance required other than regular updates.

We completed the implementation internally.

Although the ELK Elasticsearch software is open-source, we buy the hardware.

The distributed installation is the way to go.

I would rate ELK Elasticsearch a nine out of ten.

We use this solution for log management. We collect many logs from Windows systems to later analyze them for security checks and audit purposes.

I have found the sort capability of Elastic very useful for allowing us to find the information we need very quickly.

The reports could improve.

I have been using this solution for approximately three years.

The solution is very stable and reliable.

The stability is good but we have only done vertical scaling and not horizontal at this time. We collection approximately 1,000 EPS and have three people using the solution in my organization.

There has been enough support available online for what we have been using the solution for.

The initial setup was easy because we used containers. It can be challenging to implement.

We did the implementation ourselves.

We are using the free open-sourced version of this solution.

I would recommend those wanting to implement this solution use integrators or consultants. However, we did not have any problems with the installation it can be difficult.

I rate ELK Elasticsearchan eight out of ten.

While the solution is slated for making logging positions more centralized, at present we are gearing through it. A fully-fledged deployment of alignments is not yet in place.

We have adjusted the logs into the spec for a couple of our applications.

We consider all of the features to be valuable. With respect to 12B Kibana, all of the components fit in very well. Logsearch gives us certain log filtering capabilities and we can vet what we push into our database. This allows us only to log and ship limited items. Essentially, Logsearch plays a big role although not the most important one. 

The solution itself needs improvement. There is an index issue in which the data starts to crash as it increases.

This leads to an impact on the solution's stability.

The index and part of the solution's stage have weak points.

In the next release, I would like to see better plugins when integrating with, say, Microsoft Teams.

The Kibana dashboard is quite user-friendly and we have had no issues involving our technical team. However, some technical knowledge is required, especially if one wishes to create dashboards and as it relates to index management.

I have been Vusing ELK Elasticsearch for plus or minus two years.

ELK Elasticsearch is definitely a stable solution. It is the spec that surprises most of the other logging solutions in the market.

The solution is quite scalable and this is one of its advantages. We are trying to add or plug on to Elasticsearch at present.

We have been open to solutions and haven't really had a need to rely on technical support. We've relied mostly on support forums.

This said, I would rate the support well, as we initially interacted with the support team and made use of Google.

The initial setup had a bit of a learning curve for us while we acclimated ourselves to the use of the solution. However, after a while, it became quite easy. 

I would not say there was much complexity even at the outset, as we have an understanding of how to troubleshoot and do the installation.

There is more than enough documentation of the solution online. It is useful and you can find what you're looking for. There are also forums that can be of assistance. 

While I cannot say for sure, as our organization is structured so that we work in silos with everyone looking after his own infrastructure, I would estimate that we have approximately 200 employees making use of the solution.

My advice to others who are considering implementing the solution is that they first make a plan to figure out how they wish to cluster the solution and the amount of data that must be ingested. Much planning would be involved. It would be wise to start with the open-source solution, which comes with many advantages, and to move on to the Enterprise version if there should be a need for dedicated support. 

I cannot posit whether management will wish to take this route, although this is definitely worth considering, as we are talking about a fully robust infinite solution across the board. 

I rate ELK Elasticsearch an eight out of ten.

We are primarily using it for monitoring. It is used for server monitoring.

I really like the visualization that you can do within it. That's really handy. Product-wise, it is a very good and stable product.

They should improve its documentation. Their official documentation is not very informative. They can also improve their technical support. They don't help you much with the customized stuff.

They also need to add more visuals. Currently, they have line charts, bar charts, and things like that, and they can add more types of visuals. 

They should also improve the alerts. They are not very simple to use and are a bit complex. They could add more options to the alerting system.

I have been using this solution for one year.

Stability-wise, it is very good. Once the data starts coming in, it is very stable. I didn't find any big glitches in it.

We contacted their technical support once. I didn't find them very good. They are there just to provide documentation and stuff. They don't help you much with the customized stuff. They could improve that. I would rate them a two out of five.

It is complex because it is not Windows-based. It is Linux-based, so one must know Linux to deploy it properly. It is not a product that you can install with just multiple clicks. You need to understand it.

It seems good in terms of return on investment. It is a monitoring solution, and it triggers alerts before something happens. For example, it triggers an alert when the space in Windows reaches an 80% limit. I would say it is a good investment. We are able to fix things before they go wrong. If we didn't have Elasticsearch, things would go wrong, and we would be spending more time fixing them later on.

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.

I am using it to get some hands-on experience and learn the product by searching, building use cases, test cases, dashboards, and visualizations.

With hands-on experience, you learn more about the product and how it works.

It should be easier to use. It has been getting better because many functions are pre-defined, but it still needs improvement.

If you have a large enterprise environment, it is costing a lot of money and it's not a full-blown SIEM. It has SIEM features but a lot is missing. You need to involve other products to make a SIEM out of it.

Some of the other products needed were Apache, Kafka, and ticket tools. It was custom made and not what I had expected in the end.

I would like to see them get closer to a full-blown orchestrated SIEM, and create predefined modules to bring you to using it as a SIEM faster, and on the fly instead of having to tweak the Grok filter for weeks.

I would like to see more pre-defined modules.

I have been using Elasticsearch for two weeks.

We are not using the latest version, but not an old version.

It's a stable solution and we have not had any issues.

The scalability is fine.

I have contacted technical support, once or twice. The experience was okay.

The initial setup was okay, not as easy as Splunk but it was manageable.

The pricing model is questionable and needs to be addressed because when you would like to have the security they charge per machine. If you are building any cluster and you are paying €6,000 per machine, that is expensive.

I think that Elasticsearch is a good product and cheaper than Splunk.

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.