

Find out what your peers are saying about Elastic, Glean, Luigi's Box and others in Indexing and Search.
We have not purchased any licensed products, and our use of Elastic Search is purely open-source, contributing positively to our ROI.
It is stable, and we do not encounter critical issues like server downtime, which could result in data loss.
The main benefits observed from using Elastic Search include improvements in operational efficiency, along with cost, time, and resource savings.
I identified over-provisioned servers and reduced my AWS monthly bill by 15%, which is a significant saving in terms of costs.
For P1 tickets, they provide very immediate quick responses and join calls to support and troubleshoot the issue accordingly.
The customer support for Elastic Search is one of the best I have ever tried.
They have always been really responsible and responsive to my requests.
The technical support team is very helpful with complex PromQL troubleshooting.
My advice for people who are new to Grafana or considering it is to reach out to the community mainly, as that's the primary benefit of Grafana.
I do not use Grafana's support for technical issues because I have found solutions on Stack Overflow and ChatGPT helps me as well.
We can search through that document quite easily, sometimes in 7 milliseconds, sometimes one or two milliseconds.
Performance tests involving one million requests at once, we encountered issues with shards and nodes not upscaling as needed, leading to crashes and minimal data loss.
I would rate its scalability a ten.
It is highly scalable and built on a big data architecture capable of ingesting trillions of data points.
In terms of our company, the infrastructure is using two availability zones in AWS.
In assessing Grafana's scalability, we started noticing logs missing or metrics not syncing in time.
The data transfer sometimes exceeded the bandwidth limits without proper notification, which caused issues.
The stability of Elasticsearch was very high.
When you put one keyword, everything related to that keyword in your ecosystem will showcase all the results.
When something in their dashboard does not work, because it is open source, I am able to find all the relative combinations that people are having, making it much easier for me to fix.
Once you get to a higher load, you need to re-evaluate your architecture and put that into account.
Even when handling millions of data points, the visualization layer remains responsive.
From a technical point of view, there are no significant issues recalled as Elastic Search has been absolutely awesome for this use case and covers 100% of the needs.
If I need to parse one million records saved into Elastic Search, it becomes a nightmare because I need to do the pagination, and it is very problematic in that regard.
Observability features like search latency, indexing rate, and maybe rejected requests should be added to make the platform more reliable and accessible for everyone.
It would be better if they made the technology easy to use without needing to read extensive documentation.
Grafana cannot be easily embedded into certain applications and offers limited customization options for graphs.
I would want to see improvements, especially in the tracing part, where following different requests between different services could be more powerful.
On the AWS side, it is very expensive because they charge based on query basis or how much data is transferred in and out, making it very expensive.
Having the hosted solution and not having to pay for essentially a DevOps person on staff to manage makes it affordable.
You can host it on-premises, which would incur zero cost, or take it as a SaaS-based service, where the expenses remain minimal.
In an enterprise setting, pricing is reasonable, as many customers use it.
The costs associated with using Grafana are somewhere in the ten thousands because we are able to control the logs in a more efficient way to reduce it.
I purchased my Grafana Cloud subscription through the AWS Marketplace, which simplified my procurement process and allowed me to apply the cost towards my AWS committed spend.
Elastic Search makes handling large data volumes efficient and supports complex search operations.
The most valuable feature of Elasticsearch was the quick search capability, allowing us to search by any criteria needed.
The speed with which Elastic Search is able to search through all of the documents we place into it is quite remarkable, as we search through 65 billion documents in less than a second in most cases, on a constant consistent basis.
Users can monitor metrics with greater ease, and the tool aids in quickly identifying issues by providing a visual representation of data.
The fact that I can join data from my SQL database with metrics from Prometheus in the same table is a feature I have not found performed as well elsewhere.
You can check those metrics in the incident management tool by filtering the alert source as Grafana, and it helps in reducing production incidents because you can acknowledge and visualize the metrics from Grafana on time.
| Product | Mindshare (%) |
|---|---|
| Elastic Search | 10.9% |
| OpenText Knowledge Discovery (IDOL) | 6.3% |
| Lucidworks | 5.9% |
| Other | 76.9% |
| Product | Mindshare (%) |
|---|---|
| Grafana | 2.7% |
| Dynatrace | 5.5% |
| Datadog | 4.7% |
| Other | 87.1% |

| Company Size | Count |
|---|---|
| Small Business | 39 |
| Midsize Enterprise | 12 |
| Large Enterprise | 47 |
| Company Size | Count |
|---|---|
| Small Business | 13 |
| Midsize Enterprise | 10 |
| Large Enterprise | 27 |
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 like automated provisioning, high availability, security, and global reach.
Elasticsearch excels in handling time-sensitive data and complex search requirements across large datasets. Its scalability allows it to handle growing data volumes efficiently, maintaining high performance and fast response times. Integrated with Kibana, Elasticsearch enables powerful data visualization, providing real-time insights crucial for data-driven decision-making.
Elastic Cloud reduces operational overhead and improves scalability and performance, though it comes with associated costs. It is available on your preferred cloud provider — AWS, Azure, or Google Cloud. Customers who want to manage the software themselves, whether on public, private, or hybrid cloud, can download the Elastic Stack.
At its core, Elasticsearch is renowned for its full-text search capabilities, capable of performing complex queries and supporting features like fuzzy matching and auto-complete.
Peer reviews from various professionals highlight its strengths and weaknesses. Pros include its detection and correlation features, flexibility, cloud-readiness, extensibility, and efficient search capabilities. However, users have noted challenges like steep learning curves, data analysis limitations, and integration complexities. The platform is generally viewed as stable and scalable, with varying degrees of satisfaction regarding its usability and feature set.
In summary, Elasticsearch stands out for its high-speed search, scalability, and versatile analytics, making it a go-to solution for organizations managing large datasets. Its adaptability to different enterprise needs, robust community support, and continuous development keep it at the forefront of enterprise search and analytics solutions. However, potential users should be aware of its learning curve and the need for skilled personnel for optimization.
Grafana offers a customizable, user-friendly platform for robust data visualization and integration, enhancing real-time monitoring with extensive alerting and collaboration capabilities supported by an active open-source community.
Grafana stands out for its flexible dashboards and robust visualization options, integrating smoothly with tools like Prometheus. This open-source platform supports diverse environments, aiding in the visualization of IT infrastructure and business analytics. Its alerting system efficiently supports real-time monitoring. While it is praised for its community backing and cost-effectiveness, there is demand for better data aggregation, intuitive interfaces, and enhanced documentation compared to competitors such as Splunk. Simplification of configuration and the interface is sought, alongside improvements in machine learning and reporting features.
What are Grafana's most important features?Grafana is implemented widely across industries for monitoring IT infrastructure and visualizing business analytics. Companies utilize it to analyze server performance or monitor Kubernetes environments and payment transactions. The platform integrates with AWS services and other data sources to ensure observability and system health tracking, focusing on performance metrics through customized dashboards and alerts. Organizations employ Grafana to bolster observability and optimize infrastructure through robust data insights.
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