

ThousandEyes and InfluxDB compete in the network monitoring and time-series data analysis industry. ThousandEyes seems to have the upper hand due to its comprehensive monitoring capabilities, especially for large-scale operations.
Features: ThousandEyes provides comprehensive monitoring, integration with Cisco products, and an efficient alerting system. InfluxDB is known for its time-series data focus, integration with Grafana, and SQL-like query language.
Room for Improvement: ThousandEyes requires enhancements in dashboard features, integration capabilities, and cloud network path visualization. InfluxDB needs better query language support, high-cardinality data handling, and improved user documentation.
Ease of Deployment and Customer Service: ThousandEyes is typically deployed on-premises, with strong Cisco-backed support, noted for thorough integration assistance. InfluxDB deploys across on-premises and cloud environments, although improvements in support responsiveness are suggested.
Pricing and ROI: ThousandEyes, considered expensive, offers a strong ROI for large enterprises due to enhanced network performance. InfluxDB, mostly open-source, presents lower scaling costs but recent price increases are noted. Both exhibit significant ROI, yet ThousandEyes aligns better with critical large-scale needs.
These improvements translated into both cost savings and better service reliability, directly impacting business outcomes.
It simplifies processes and reduces the need for additional employees.
It has reduced a lot of time in terms of troubleshooting because the way it produces the data on a time-series basis allows me to collect and store the data for future reference.
There has been a great ROI from using ThousandEyes, with significant time saved in troubleshooting as I can quickly pinpoint issues rather than spending time isolating them, alongside enhancing customer feedback and experience.
I have seen a return on investment by reducing troubleshooting time and having lesser user mapping error issues, in addition to engineering time saved through better observability and reduced organizational MTTR.
They get on a call, resolve issues, and handle everything efficiently.
The InfluxDB support team was knowledgeable and helped us troubleshoot complex problems efficiently.
Obtaining that quantity of data directly from InfluxDB is quite challenging, and that is why we ask for help from the InfluxDB team to retrieve the data to avoid timeouts and those kinds of issues.
We contacted the support team, and they resolved it within a couple of hours.
I would give it a rating of 10 because whenever we have any issues, we can typically reach someone who has the knowledge to help us.
The customer support for ThousandEyes is very proactive and supportive.
The main challenge with InfluxDB, which is common with all databases, was handling very high throughput systems and high throughput message flow.
It can handle large volumes of time-series data and with high ingestion rates, making it suitable for enterprise-scale deployments.
We’ve scaled on volume with seven years of continuous data without performance degradation.
Scalability with ThousandEyes is straightforward as you don't really need to scale; it's designed to monitor multiple applications, accommodating 50 or 100 applications simultaneously.
ThousandEyes's scalability is excellent; it is very scalable and grows with my organization's needs.
It serves as the backbone of our application, and its stability is crucial.
We have used it to support mission-critical systems with continuous data ingestion and real-time analytics.
It is very stable, with no reliability or downtime in InfluxDB.
From my experience, ThousandEyes has been stable up to 95%; I have not seen any stability issues.
ThousandEyes is not very stable; sometimes you have to reboot the servers to get actual results.
I would assess the stability and reliability of ThousandEyes as good, with no downtime or crashes or performance issues experienced.
InfluxDB deprecated FluxQL, which was intuitive since developers are already familiar with standard querying.
Having a SQL abstraction in InfluxDB could be beneficial, making it more accessible for teams that prefer querying with SQL-style syntax.
It could include automated backup and a monitoring solution for InfluxDB or a script developed by a REST API.
Incidents should be alerted on and traced early, before they escalate to full outages.
I think the pricing, setup cost, and licensing for ThousandEyes are too costly.
Having a dedicated incident alert system for URL alerts would help manage noise and streamline operations, especially during patch upgrades.
We use the open-source version of InfluxDB, so it is free.
I find the cloud version pricing of InfluxDB reasonable, and for the on-premises solution we use in our service, we need to purchase licenses.
Pricing is based on data volume, retention, and features, which really makes it scalable but requires careful planning to avoid unexpected costs.
My experience with pricing, setup cost, and licensing has been that everything was cost-effective.
My experience with pricing, setup cost, and licensing is that it comes in cheaper than alternatives.
My experience with pricing, setup costs, and licensing indicates that licensing is somewhat complicated because of the credits system.
The most important feature for us is low latency, which is crucial in building a high-performance engine for day trading.
InfluxDB’s core functionality is crucial as it allows us to store our data and execute queries with excellent response times.
It helps me maintain my solution easily because it is very reliable, so we didn't face any performance issues or crashes regarding our queries; we can get the results very fast.
I measure the 70% improvement in customer experience through customer tickets and feedback after resolving issues, where previously, users faced problems and limited time on the platform, and after using ThousandEyes, the user time reached up to five to six hours a day, even for teams possibly totaling 30 hours a day.
ThousandEyes offers the best features including global internet and cloud visibility from distributed vantage points, application and network performance monitoring, real-time outage detection and incident alerts, end-to-end path visualization for rapid troubleshooting, proactive issue demarcation, and historical data.
ThousandEyes has become critical for swift network troubleshooting as well, so anytime that there's potential issues with applications or we want to be proactive in resolving potential issues before they arise, ThousandEyes is really the platform that we're leveraging for WAN monitoring, Wi-Fi, latency, packet loss, etc.
| Product | Mindshare (%) |
|---|---|
| ThousandEyes | 1.7% |
| InfluxDB | 0.5% |
| Other | 97.8% |


| Company Size | Count |
|---|---|
| Small Business | 9 |
| Midsize Enterprise | 5 |
| Large Enterprise | 9 |
| Company Size | Count |
|---|---|
| Small Business | 8 |
| Midsize Enterprise | 3 |
| Large Enterprise | 17 |
InfluxDB offers efficient time series data handling with fast writes, optimized storage, and seamless Grafana integration, making it ideal for high-volume applications like crypto trading and real-time monitoring. Its SQL-like query language and cloud-based options enhance user experience and system scalability.
InfluxDB stands out with its ability to handle high-volume time series data efficiently, thanks to fast data writes and efficient compression. It is highly scalable, providing clustering features for improved performance management. Integration with Grafana enhances visualization, making it easier to analyze complex data through a user-friendly SQL-like query language. Real-time monitoring, historical data access, and proactive alerts enhance system reliability. Its cloud offering simplifies maintenance and operations, making it attractive for users seeking an efficient time series database.
What are the key features of InfluxDB?InfluxDB is applied extensively in industries handling high-volume data needs. For sensor data storage in production environments, it offers reliable performance. Its role in server management metrics and performance monitoring is crucial for maintaining optimal operations. In crypto market data collection, it supports fast-paced trading environments. Industries use it for real-time tracking, like maritime vessel monitoring, leveraging its rapid data handling and visualization capabilities. Its applications also extend to IoT environments, API performance tracking, HVAC systems, and log aggregation, often integrating with Prometheus, Docker, and AWS to enhance system capabilities.
ThousandEyes offers cutting-edge monitoring capabilities with advanced features such as end-to-end network monitoring, real-time alerts, and application insights. It supports integration with Cisco products and provides visibility into network paths, helping businesses maintain superior network performance.
ThousandEyes is renowned for its ability to diagnose network issues by offering comprehensive network path visualization and detailed analytics. Its ability to detect packet loss and monitor ISPs ensures robust network security. The integration capabilities, particularly with Cisco platforms, make it versatile for businesses requiring customizable dashboards. Users benefit from ease of use and real-time alert systems, though improvements in guest portal usability, packet analysis, and integration with Cisco platforms are needed. Enhancements in automation, knowledge resources, and application-level features could benefit users, alongside better network device monitoring through SNMP and improved path visualization. Additionally, better incident management and alert detection systems are anticipated.
What are the key features of ThousandEyes?Businesses across sectors leverage ThousandEyes for seamless network monitoring and diagnostics. It is invaluable for ensuring connectivity across LANs, Wi-Fi, internet, and SaaS applications. ThousandEyes provides critical insights into internet and ISP performance, significantly benefiting industries reliant on robust digital infrastructure.
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