External reviews are not included in the AWS star rating for the product.
My main use case for InfluxDB involves gathering metric data from our storage clusters and putting them into Grafana dashboards, so InfluxDB is the data source for Grafana.
I collect and display metrics in Grafana such as throughputs, IOPS, latencies, quota consumptions, network and cart errors.
Regarding my main use case, there are no particular challenges; we run our scripts every five minutes, so we gather data from our clusters every five minutes and keep more than six months.
The best features InfluxDB offers include a web UI that I love because sometimes I need to check some details about my metrics, enabling me to easily see simple details on it.
While the API does not stand out to me since we don't use it regularly for InfluxDB, we primarily use it as a data source for Grafana.
InfluxDB has positively impacted my organization by being a part of our solution, which helps us maintain our solution easily.
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 believe InfluxDB can be improved, but I'm not sure how; maybe some people can say more than me, but for myself, it is enough.
I don't have any additional improvements to suggest regarding documentation, UI, or anything else that I wish was different; nothing comes to mind.
I have been using InfluxDB almost for two years.
InfluxDB is stable.
We haven't faced any issues with InfluxDB's scalability; maybe our capacity consumptions are small, or it is simply good enough to handle that much capacity.
I did not previously use a different solution; there was no switch required.
We do not purchase InfluxDB through the AWS Marketplace; instead, we use the open-source version.
I haven't seen a return on investment; unfortunately, I cannot share relevant metrics such as time saved, fewer employees needed, or money saved.
I'm not sure about the details regarding pricing, setup cost, and licensing.
Before choosing InfluxDB, I only evaluated Prometheus, but it is not the right solution for us because it has a different methodology than InfluxDB, which exactly matches our requirements.
My advice to others looking into using InfluxDB is that if they need any time-series database, InfluxDB is a good solution with its stable, high performance, and scalable capabilities, and I love the web UI, which also allows us to create dashboards without any other third-party tools.
On a scale of one to ten, I rate InfluxDB a ten.
I have been using InfluxDB for one year for my project, Greenhouse Management using Embedded System, to represent the sensor data on a web dashboard.
I have used InfluxDB for storing the data and representing it on a web dashboard for my greenhouse project, and that is the only thing I have used InfluxDB for.
InfluxDB offers a database similar to an Excel data sheet, where we can select different data in different fields.
The Excel-like feature of InfluxDB will be beneficial for my greenhouse project, in which I have divided data of different sensors in different boxes so that it is easy to locate that box and view data.
I have successfully completed my greenhouse project with the help of InfluxDB to visualize the data in the dashboard, and it is beneficial for me.
Visualizing my data on a web dashboard helps, as it also gives the data of how it is changing with time, and it also stores data for the future for AI.
It's pretty much good regarding my use case, but I want to tell you that the interface of InfluxDB is so complex and should be made easier for non-technical people.
With InfluxDB, I have to use Grafana, which provides good visualization, so I will tell you that mixing Grafana and InfluxDB would make visualization better in InfluxDB.
Documentation is also required for InfluxDB, as I haven't got the documentation related to this, but there is a video on Udemy that helped me to use InfluxDB effectively.
I have been using InfluxDB for one year for my project, Greenhouse Management using Embedded System, to represent the sensor data on a web dashboard.
It is very stable, with no reliability or downtime in InfluxDB; it is very good.
I have normally used InfluxDB and not utilized much scalability, so I haven't experienced the scalability of InfluxDB.
I don't know about the customer support of InfluxDB as I haven't needed help; that's why I haven't experienced customer service.
I haven't used any other solution than InfluxDB, as I appreciate InfluxDB very much.
I haven't evaluated any other options, as I appreciate InfluxDB, which is why I have chosen InfluxDB.
InfluxDB reduced my time to show data without any interruption, also reducing the number of people needed to manage the project; it is very good to have InfluxDB in my project.
I rate InfluxDB a seven out of ten.
It's good, which is why I have chosen it more than five, but it is not rated higher because I have to use Grafana with InfluxDB. I think if it gave visualized data in a better way, then it would have been rated more than seven.
If you want a normal, good visualization or database management system, you can go for InfluxDB, as it is very good software that can visualize the data.
InfluxDB is the main component in our large enterprise-scale streaming data application for maritime vessels. We collect position data from vessels around the coast once per second, put it on a Kafka stream, and feed those positions into InfluxDB continuously. This has been working flawlessly since 2018. We have seven years of time-series data for all the vessels that my company operates, roughly 130 to 140 vessels. Every move they make is being tracked and stored in InfluxDB.
We mainly write and read data from InfluxDB. We perform very simple queries to do time series on a key, which is a unique ID of the vessel. We will select a vessel and select from time to time stamp. That’s what we do. InfluxDB’s core functionality is crucial as it allows us to store our data and execute queries with excellent response times.
It is challenging to get long-running backups while running InfluxDB in a Microsoft Azure Kubernetes cluster. Replicating data for on-prem development and testing is difficult. Having a SQL abstraction in InfluxDB could be beneficial, making it more accessible for teams that prefer querying with SQL-style syntax.
In total, I've been using InfluxDB for six years.
InfluxDB is extremely stable. It serves as the backbone of our application, and its stability is crucial. If InfluxDB stops or doesn’t scale, the entire application stops.
Scalability is critical. We’ve scaled on volume with seven years of continuous data without performance degradation. The scalability allows us to track vessel movements per second back to the application's conception in 2017.
We did not use a different solution for these use cases before InfluxDB.
The initial setup can be intimidating for newcomers, and there is a certain threshold needed due to the performance we get. However, once familiar with the setup, it becomes streamlined.
Four people were involved in the deployment process, and one person is now needed for maintenance.
We haven't gauged any measurable benefits; our company is more operational-focused.
We use the open-source version of InfluxDB, so it is free.
We evaluated using PostgreSQL and a time-series database in Amazon, though I can't recall its name.
InfluxDB works as expected with excellent scalability and stability, which is critical for our application. I rate InfluxDB ten out of ten overall.
Neutral
This review does not judge the InfluxDB product itself, but this AWS Marketplace offering.
For our company, we did not manage to get this product working. Creating the AWS Marketplace linked account at InfluxData always failed with a 500 server error at Influx, resulting in a free-only account, which was not fully functional.
Even working for 4 weeks on this topic together with the influx support team, with several emails and web-meetings, did not help. The influx development team could not identify and solve the issues.
I use the solution to store and manage data from various sensors in a production environment. I have developed a system where data from these sensors is communicated through an OPC UA receiver and stored in InfluxDB. It handles serial data from sensors effectively and integrates well with Grafana for visualization.
The platform operates very quickly. It is easy to configure, connect, and query and integrates seamlessly with Grafana.
I have been using InfluxDB for four years.
I have not experienced any stability issues with the product.
Approximately 20% of our team uses InfluxDB.
I recommend InfluxDB to others and rate it a ten.
InfluxDB is a database where you can insert data. However, it would be best if you had different components for alerting, data sending, and visualization. You need to install tools to collect data from servers. It must be installed on Windows or Linux servers. During installation, ensure that the configuration file is correct to prevent issues. Once data is collected, it can be sent to InfluxDB. For visualization, you can use open-source tools like Grafana.
InfluxDB is generally stable, but we've encountered issues with the configuration file in our ticket stack. For instance, a mistake in one of the metrics out of a hundred KPIs can disrupt data collection for all KPIs. This happens because the agent stops working if there's an issue with any configuration part. To address this, it is essential to ensure that all configurations are part of the agent's EXE file when provided. This makes it easier to package the agent for server installation and ensures all KPIs are available from the server. Additionally, the agent cannot encrypt and decrypt passwords for authentication, which can be problematic when monitoring URLs or requiring authentication tokens. This requires additional scripting and can prolong service restart times.
I have been working with the product for five years.
My company has 20-30 admins and 4,000-5,000 users. We have around 15,000 servers.
If you deviate from their documentation, they may refuse to provide support, stating it's not covered under the agreement. Additionally, their response times are slow, and they often suggest purchasing premium support for quicker resolution.
When you opt for premium support, they usually assign dedicated consultants. This means that whenever you encounter a problem, you have direct access to experts whom you can call, email, or engage in a call to resolve issues.
The tool is an open-source product.
If you're considering using InfluxDB for the first time, I recommend trying it. It's an open-source database with the option to purchase enterprise support.
When purchasing the TICK stack, I recommend you opt for premium support. Premium support can be beneficial, particularly when encountering configuration issues or other challenges. With premium support, you can quickly reach out for assistance via phone and work towards resolving any issues promptly. Otherwise, you may wait for up to another week to resolve the problem.
Learning to use InfluxDB is not necessarily easy for a beginner. It requires some understanding, especially in areas like automation and scripting.
I would rate it as an open-source tool around seven to eight out of ten. You only need to spend money on the resources, not much on the product itself. Essentially, you need to invest in the database.
Initially, we used Prometheus and Grafana for alerts. But, it wasn't feasible to handle logs and other types of databases. We then switched to InfluxDB due to its user interface, which allowed us to customize alerts, data visualization, and filtering for monitoring purposes.
The user interface is well-designed and easy to use. It provides a clear overview of the data, making it simple to understand the information at hand.
There were concerns about data loss due to infrastructure limitations. We couldn't back up data locally if we were using the InfluxDB cloud, which was a major drawback. So, InfluxDB could improve its data backup capabilities.
Having a backup option would allow us to save data and avoid relying solely on cloud infrastructure. We've experienced data loss incidents in the past, so backup is crucial. I've tried both on-premises and cloud-based deployments, and each has its limitations.
I used this solution for one and a half years.
I would rate stability at seven. We faced two to three incidents where we lost data.
Scalability is good, but I would give it six out of ten. It's not very stable regarding data backup. We had a user who worked with the support team, and they helped a lot, but they couldn't retrieve the complete data quickly.
We had a user who worked with the support team, and they helped a lot, but they couldn't retrieve the complete data quickly.
The support team is good, but if they don't have the data, it's not their fault. It's the technical team's issue.
Positive
I use Datadog, New Relic, Grafana and Prometheus. I switched to Influx DB because of its user interface.
The initial setup is very straightforward. It is not very tricky.
I have tried both versions for on-premises and cloud deployment. Otis took around five to six minutes. If we have a script, cloud deployment takes one to two minutes.
InfluxDB recently increased its price. It is very expensive now. It is now per month; earlier, it was per year-based license.
Overall, I would rate the solution a seven out of ten because InfluxDB needs to remove the limitations so users can see all their data. This was a huge headache for me because we got hit twice or thrice.