Elastic Stack Reviews & Product Details

Elastic Stack offers an excellent combination of real-time search, analytics, and visualization capabilities. Elasticsearch’s full-text search is incredibly fast and scalable, Logstash provides robust data ingestion pipelines, and Kibana makes it easy to create rich, interactive dashboards. Its open-source nature and large community are also major strengths, allowing for flexible customization and broad plugin support. It seamlessly integrates with other tools and supports a wide range of data formats. Review collected by and hosted on G2.com.

While Elastic Stack is powerful, it can be resource-intensive, especially as data volume grows. Managing clusters and ensuring optimal performance may require deep expertise, particularly with memory and disk usage. The learning curve can be steep for beginners, and commercial licensing for advanced features like machine learning can get expensive. Additionally, troubleshooting Logstash pipelines sometimes lacks clarity and good debugging tools. Review collected by and hosted on G2.com.

Elastic Stack offers a seamless way to collect, search, analyze, and visualize logs and metrics from disparate systems. The integration between Elasticsearch, Logstash, Beats, and Kibana (ELK) is smooth and highly configurable. Its flexibility across different deployment models — self-managed, cloud, hybrid — is extremely valuable. Kibana’s dashboards are powerful for building real-time visualizations and alerts. Review collected by and hosted on G2.com.

So far, I haven’t encountered any significant issues or limitations with Elastic Stack. It has performed reliably across use cases, and the documentation and community support have been strong. Any learning curve or complexity has been manageable with proper setup. Review collected by and hosted on G2.com.

I like best about Elastic Stack is its speed and flexibility Review collected by and hosted on G2.com.

Elasticsearch clusters require a lot of memory, storage, and CPU, which can make it expensive at scale Review collected by and hosted on G2.com.

Kibana is an open source data visualization plugin for Elasticsearch. It provides us with a way to easily create and share beautiful dashboards filled with dynamic charts, graphs, and maps. It makes it easy to find insights in your data, and since it's fully integrated with Elasticsearch, you can use it to search, analyze, and visualize your data all in one .It's a definite recommendation for data analysis because it's so user-friendly and versatile. Review collected by and hosted on G2.com.

Major complaint is that it can be slow to load data sets, particularly those that are large. Additionally, I find the built-in visualizations confusing and difficult to use. It also does not currently have a way to export charts and graphs Review collected by and hosted on G2.com.

Since I started using the Elastic Stack, I found it incredibly helpful. It makes it very easy to find the specific logs you want to see, thanks to its simple UI. Once you understand its features, it becomes effortless to use in your daily work. What amazes me the most is how fast it performs, especially as a programmer myself. I use it daily because, with Elastic, finding anything in production is quick and straightforward, and it's also very easy to integrate. Review collected by and hosted on G2.com.

The thing which I dislike about the elastic stag was if we have some such criteria and behalf of that we have some result so if we want the particular thread which are come across or which are nearby to the thread which was in result is not easily accessible also the server are many as I already mention altho is someone there to guide you it is very easy to understand and start working on elastic stack the difficulty I have face while using elastic stack it was in starting when I started using elastic stack there was many servers and I am not aware which want to use for the production and which one to use for test environment if some one read the documentation i think it will be very easy to understand in starting it self Review collected by and hosted on G2.com.

Support for storing vector data.

Elastic security (SIEM) - Lot of integrations and more than 1000+ EDR rules and machine learning jobs.

Easy to setup monitoring and observability Review collected by and hosted on G2.com.

More support for KNN Queries similar to normal full text search queries.

Everything which we can do in normal full text queries must be possible using KNN as well.

More examples for implementing Crawler for the first time - With Real use cases like, how to crawl certain URLs, PDFs, etc. Review collected by and hosted on G2.com.

1. It's very usefull tool to analyse the data and to trouble shoot HW

2. It has got lot of features which are useful to analysis the data

3. Elastic is very useful while working on customer support to gather the data and to solve the problem

4. Very easy to integrate with internal tools

5. We use elastic frequentyl and regularly to analyse the data Review collected by and hosted on G2.com.

1. Nothing much to dislike, its important use all feature to explore more options Review collected by and hosted on G2.com.

Open sourced, a lot of common issues could be found online. It's quick to integrate existing workloads for monitoring, and scaling and backip is well managed. Review collected by and hosted on G2.com.

Some enterprise features are hard to configure in the managed hosting version, e.g. setting up SAML requires me to upload a custom plugin bundle while it should be configurable out of the box with it's UI. Review collected by and hosted on G2.com.

Elastic stack gives us the ability to aggregate logs from all our systems and applications, analyze these logs, and create visualizations for application and infrastructure monitoring, faster troubleshooting, security analytics, and more.It is very easy to use and implement and it easily gets integrated with various other tools in Cyberspace.

The logs can be used to generate graphs and representations on the dashboards which can be used by various teams as a central point of reference to drive the governance. Review collected by and hosted on G2.com.

Elastic Stack software is free to use, but building, growing, and maintaining the Elastic Stack requires infrastructure and resources. Whether you deploy on-premises or in the cloud, your costs for computing and data storage will depend on:

The total log volume you aggregate daily from all applications, systems, and networks.

How long you will retain data for either indexing or archiving.

Also, there is some latency to populate the graphs at times and this needs to be fixed to have a good end user experience. Review collected by and hosted on G2.com.

One of the standout features of Elastic Stack that I particularly appreciate is its ability to seamlessly handle data at scale while offering a wide range of powerful functions.

First and foremost, Elastic Stack's search and analytics capabilities are exceptional. With Elasticsearch as the core component, it provides lightning-fast search results and performs complex analytics on large volumes of data with impressive efficiency. Whether it's searching through vast amounts of textual information, aggregating and visualizing data, or performing advanced analytics, Elastic Stack's search functionality is highly robust and flexible. Review collected by and hosted on G2.com.

While Elastic Stack offers numerous powerful features, there are a few areas where it may have some limitations or drawbacks.

One aspect that can be challenging is the complexity of configuration and management. Elastic Stack consists of multiple components, each with its own configuration settings and dependencies. Configuring and fine-tuning the stack to suit specific requirements can be time-consuming, especially for users who are new to the system. Additionally, managing a distributed deployment with multiple nodes can be complex, requiring careful planning and expertise to ensure optimal performance and reliability. Review collected by and hosted on G2.com.