eG Enterprise and VictoriaMetrics compete in performance monitoring and data storage. VictoriaMetrics appears superior due to its scalability and cost-effectiveness in managing time-series data.
Features: eG Enterprise delivers in-depth end-to-end visibility, real-user monitoring, and advanced analytics suitable for enterprise-level needs. VictoriaMetrics efficiently manages large-scale time-series database tasks with high ingestion rates and query performance, providing greater efficiency for data-heavy applications.
Ease of Deployment and Customer Service: eG Enterprise offers a personalized deployment model with comprehensive support options, enhancing customer satisfaction. VictoriaMetrics provides straightforward deployment but relies more on community resources for support.
Pricing and ROI: eG Enterprise generally involves higher setup costs due to its extensive feature set and personalized service, appealing to enterprises needing detailed analytics and justifying the investment with high ROI. VictoriaMetrics offers a cost-effective solution suited for organizations focusing on time-series data management, translating to favorable ROI.
Our customers see excellent return on investment because eG Enterprise helps anticipate problems, saving money in the long run.
I'm also very satisfied with the integration of eG Enterprise into the APIs, into trouble ticketing, and into advanced reporting.
I have seen a return on investment with VictoriaMetrics, saving 40% in storage costs compared to Prometheus, reducing query latency by 60%, and cutting maintenance time by half.
time was saved due to simplicity and a shorter learning curve compared to other tools.
Because VictoriaMetrics runs more efficiently and much faster, debugging an issue or understanding system performance is much easier.
I would rate their technical support for eG Enterprise probably as the best I've ever dealt with.
We reached out once or twice for minor issues during the initial setup and integration, and they were helpful in resolving the issues.
VictoriaMetrics customer support is exceptional.
We use the open-source version of VictoriaMetrics, so we did not require any customer support.
It handles large volumes of time series data efficiently, using less memory and disk compared to Prometheus or Thanos.
We deploy and embed it in our Helm chart and it works out of the box.
VictoriaMetrics has handled increases in data and users smoothly so far.
In terms of accuracy and reliability, VictoriaMetrics's output is pretty sufficient and works very well in a native Kubernetes setup, which I appreciate.
The components are simple, restarts are fast, and stateless parts can be replaced without data loss.
Regarding stability, I would rate it a ten out of ten.
For small and medium businesses, eG Enterprise is usually too expensive.
I think the overall licensing models of eG Enterprise could be changed and adapted to a more flexible, more agile structure.
For our use cases, it is a really good offering, and while we would be interested to see what else it brings in the future, at this point in time it checks all our boxes and we are quite satisfied with it.
VictoriaMetrics is quite a good project and quite easy to use overall.
I compared it with my experience on other time series databases, and it has a huge advantage, so I do not see the need for urgent improvements or optimizations.
The pricing is per user per year and varies depending on the components being monitored.
We did not require any license for VictoriaMetrics since we are using the open-source version.
I used the free open-source version, and it was sufficient for my needs.
My experience with pricing, setup cost, and licensing for VictoriaMetrics is positive since it is open-source under Apache 2.0, so there is no licensing cost.
The data gathering capabilities and the automation, which utilizes artificial intelligence, are the most valuable features.
User satisfaction with eG Enterprise is really the key component now, so if you go to VDI or RDH, any of those platforms, you get the total end-to-end user experience because they do have endpoint monitoring now as well, and that was the feature that was lacking before.
The best aspect of using VictoriaMetrics is the reduction in resources including RAM, memory, disk, and other infrastructure requirements, which have all decreased substantially after implementation.
In my experience, the best features VictoriaMetrics offers include that VM agent does its work very efficiently and does not use a lot of resources.
Its compact storage and fast query performance make it ideal for long-term metric storage.
| Product | Mindshare (%) |
|---|---|
| VictoriaMetrics | 0.3% |
| eG Enterprise | 0.8% |
| Other | 98.9% |
| Company Size | Count |
|---|---|
| Small Business | 9 |
| Midsize Enterprise | 1 |
| Large Enterprise | 11 |
| Company Size | Count |
|---|---|
| Small Business | 3 |
| Midsize Enterprise | 2 |
| Large Enterprise | 2 |
eG Enterprise is a comprehensive tool offering end-to-end monitoring across applications, infrastructure, and Citrix environments through a single visual interface, simplifying diagnostics and configuration.
eG Enterprise provides a robust platform that integrates monitoring and diagnostics capabilities for diverse IT landscapes. Users benefit from a centralized view of applications and infrastructure, bolstered by visual topology maps and intuitive data presentation. The auto-configuration feature ensures efficient setup, while its AI-based automation drives superior data analysis and insights. Though challenges exist in interface modernization and configuration complexity, its scalability and real user experience insights make it a strong contender for IT management. Companies place high value on its seamless integration with ITSM and ability to track user behavior, despite some limitations in OpenShift and complex backend configurations.
What are the important features of eG Enterprise?eG Enterprise is leveraged extensively in monitoring Windows platforms and servers, assisting in troubleshooting and application performance analysis. It facilitates real user monitoring of business services across Saudi Arabia. Organizations use it for Citrix and synthetic web application monitoring, as well as database and network management. Consultants find value in deploying it on-premises for their clients, aiding in diagnosing code-level issues effectively.
Teams that switch to VictoriaMetrics report 70% less RAM and 75% less disk (verified PeerSpot user reviews), and cloud bills up to 10x lower (Grammarly case study) — while keeping their existing dashboards and alerting rules working. It is an open source observability solution for metrics, logs, and traces: a drop-in replacement for Prometheus and other backends that keeps scaling when data volume, query speed, or cost no longer does. It runs anywhere — from a Raspberry Pi to thousand-core clusters, on-premises or in the cloud — and is Kubernetes- and OpenTelemetry-compatible. Built by engineers, for engineers: Over 1B Docker pulls, 19M GitHub downloads, and 27K+ GitHub stars. Simple, reliable, and efficient observability for everyone.
VictoriaMetrics delivers observability in two complementary forms. The open source products are complete, production-grade, and free to run at any scale. Enterprise builds on that same code with capabilities and support for the most demanding environments — it extends open source rather than gating it.
Open source. VictoriaMetrics is a high-performance time series database and monitoring solution, compatible with PromQL via MetricsQL, so existing Prometheus dashboards, recording rules, and alerting rules keep working. VictoriaLogs is a logs database for mission-critical logging, and VictoriaTraces stores and queries distributed tracing data. All three are engineered for minimal RAM, disk, and compute at high ingestion rates.
Enterprise. VictoriaMetrics Enterprise adds features for large, multi-team deployments — plus direct support from the engineers who build the product, with architectural and security guidance. VictoriaMetrics Cloud is the same solution fully managed, and VictoriaMetrics Anomaly Detection applies machine learning to cut alert noise, so the alerts that do reach your team in Slack or on their phones are the ones that matter.
Measured results from users. PeerSpot reviewers report roughly 70% lower RAM use, 75% lower disk use, 3x faster writes, and 7x faster p95 query latency after replacing Prometheus. Grammarly cut its monitoring-related AWS bill about 10x; Granulate reduced metrics storage costs about 5x after moving from Grafana Cloud (Mimir).
Why teams choose VictoriaMetric
What are the key features of VictoriaMetrics?
What benefits and ROI should users expect?
Top use cases
VictoriaMetrics runs in production across finance, telecommunications, energy, scientific research, and IoT — from CERN's particle physics experiments to IHI Terrasun's utility-scale battery storage to Grammarly's product infrastructure. Wherever real-time telemetry at scale is critical, it delivers simple, reliable, and efficient observability for everyone. By engineers, for engineers.
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