Elastic Search Reviews

I'm a data scientist and we're a customer of ELK. We use the solution for multiple projects, mainly based around customer analytics.

I value the feature that allows me to share dashboards with different people with different levels of access. They can perform their own queries, like adjusting the time filter or hitting some other filters. It's very useful.

In terms of product improvement, ratio aggregation is not supported in this solution. I can do aggregations, but taking a ratio of two metrics is not supported. That's a common use case that I have come across. And if I want to do bulk coding then that's something that is not very convenient. I would like those things to be included in the next version. 

I've been using this solution for three years. 

Occasionally when you're handling large data you get some out of memory exceptions from time to time. It happens when you're doing pairing. Sometimes a few shots will fail. These are all typically when you're doing things on cloud on a large scale they tend happen.

It's a scalable solution. For now, we have about 10 users and we plan to increase that number. We use it regularly. 

I haven't needed to contact technical support. The forums are pretty good and most of the things that I need to ask are already answered so no need for support. The documentation and forums were enough. 

I haven't used other solutions. 

The initial setup is straightforward, it took about an hour. I did the setup myself. Some others also did it themselves and we had developers who put it up in the cloud for the others. 

We are currently using the Open Source version, so we didn't need to offset any licensing. For now, it's just the cost of maintaining the server. 

Our tech team did the research and I don't know if there were other options considered. 

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. 

We use this solution to collect log data and analyze it. We have an on-premises deployment.

The special text processing features in this solution are very important for me.

As a system, it is easy to use.

This is not a robust system, so in terms of resilience, they have to make some improvements. From time to time the system goes down and we have to start again, after adjusting some configuration parameters.

Technical support can be improved.

The interface would be improved with the inclusion of dashboards to assist in analyzing problems because it is very difficult. Better dashboards or a better configuration system would be very good.

This is not exactly a stable solution, which is why we are considering another compatible tool, and whether we go on with Elasticsearch or change it.

I follow their forum and blogs, and I have also asked questions directly to their technical department. I would say that support is moderate. It is not very good or very bad, but in between.

We did not use another solution prior to this one.

The initial setup of this solution is easy and straightforward.

The deployment is both easy and quick.

We have an in-house team that handles deployment.

Two people are enough for deployment and maintenance.

We did not evaluate other options before choosing this solution, but due to issues with stability, I'm now trying out PostgreSQL for comparison.

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.

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.

The primary use case of this solution is for text indexing and aggregating logs from different microservices.

-Scalability and resiliency

-Clustering and high availability

-Automatic node recovery

Kibana should be more friendly, especially when building dashboards.

Stability needs improvement.

I would like to see the Kibana operating more smoothly, as Grafana does. Also, I would like to see some improvements with the machine learning capability, so that we can rely on it more. It's in the early phases but this would be a great way to start using it.

When it comes to aggregation and calculations, I would like to have to have advanced options in the dashboards to be used in a simplified way, such as building formulas and queries between different fields and indexes.

Alerting feature should be more flexible with advanced options.

I have been using Elasticsearch for approximately five years.

This solution is stable, but at times the stack will freeze and you have to remove and recreate the cluster. It may be an issue related to AWS.

We have not had any issues with the scalability.

We have not had any issues with technical support.

Datadog, it's expensive when it comes for a big infrastructure and cannot be self hosted when it comes to specific sensitive cases.

The initial setup was fast. We have the provisioning, which made it fast and easy.

It can be expensive. When managed by AWS you have different options and features that are locked and not available to you on the Kibana and security levels.

You cannot use the full X-Pack feature set when you go through AWS.

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.

What we use this ELK (Elasticsearch, Logstash, and Kibana) solution is mostly for keeping firewall logs and collecting traffic flow information.

The scalability of this product is something that is very impressive and the performance is also very good.

I think the GUI part of the solution has the most room for improvement. Actually, we are using the free version. We do not use the plug-ins so we have to do some additional development ourselves to have the necessary access to the controls.

We are not a heavy user, we just keep the logs and track data in the system. We use it and there is no problem for our current purposes and level of use.

We have been working with the solution for just over a year.

Up until this point, there have been a few times that we did have some issues and we did not know what went wrong. But we have a guy who is dedicated to managing the system now and it is running pretty well. At this point, we do not have to spend much time in administration and maintenance paying a lot of attention to it. I would say it is pretty stable, overall.

We have around five people involved in using the solution.

The scalability is very impressive. We can do a lot of things with the product and have not explored all the possibilities as it is something we use somewhat lightly compared to its potential.

We do not yet currently use a full technical support plan. We are not really using the product extensively enough to warrant that expenditure. Up until now, our use has been light and the product is not heavily burdened. It has been performing as expected. When we upscale usage we will probably engage with a paid support plan.

The initial setup is not that problematic. It is obviously manageable as we are doing it by ourselves, so it is okay and fairly straightforward. We didn't need any assistance from integrators or consultants for the deployment.

Before choosing to go in this direction, we actually checked with some of the database options like the JSON option and Mango. The Elasticsearch product was referred to us by a friend at another company as a better solution for our particular need. They are using the system. After some tests and reviews of the products, we thought it would fit our needs, so we decided to go with it.

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.

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.

I use Elasticsearch with Logstash and Kibana.

The most valuable features are the data store and the X-pack extension.

The user interface is ok.

The integration of Elasticsearch, Logstash, and Kibana is very good.

The pricing of this product needs to be more clear because I cannot understand it when I review the website.

This solution is scalable.

I rely on the community for technical support.

The initial setup of this solution is a little bit hard. I did not find it hard, myself, but it was difficult for my colleague who had less experience.

The deployment takes between one and two hours.

We implemented this solution ourselves.

The pricing of this solution is not clear.

This solution is ok for me and my business.

I would rate this solution an eight out of ten.

• Fast search
• Relevant results returned
• Autocomplete/fuzzy search

• Search 
• To implement the main requirements regarding my support portal.

Machine learning on search.

No issues. It is very stable.

No issues. It is easy to scale with the cluster node model.

I would rate technical support with a nine out of 10. Support is very reactive and proactive.

We did have a previous solution. It was a monster to install and configure.

The initial setup was straightforward.

The pricing and license model are clear: node-based model. 

We evaluated Solr.

The search product is a product exposing API. Therefore, be comfortable in developing your own front-end to integrate the Search API.