Has supported long-term metric tracking and fast data access for performance monitoring
What is our primary use case?
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.
What is most valuable?
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.
What needs improvement?
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.
For how long have I used the solution?
I have been using InfluxDB almost for two years.
What do I think about the stability of the solution?
What do I think about the scalability of the solution?
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.
Which solution did I use previously and why did I switch?
I did not previously use a different solution; there was no switch required.
How was the initial setup?
We do not purchase InfluxDB through the AWS Marketplace; instead, we use the open-source version.
What was our ROI?
I haven't seen a return on investment; unfortunately, I cannot share relevant metrics such as time saved, fewer employees needed, or money saved.
What's my experience with pricing, setup cost, and licensing?
I'm not sure about the details regarding pricing, setup cost, and licensing.
Which other solutions did I evaluate?
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.
What other advice do I have?
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.
Which deployment model are you using for this solution?
Hybrid Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Tracking vessel movements seamlessly with continuous data collection and query execution
What is our primary use case?
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.
What is most valuable?
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.
What needs improvement?
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.
For how long have I used the solution?
In total, I've been using InfluxDB for six years.
What do I think about the stability of the solution?
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.
What do I think about the scalability of the solution?
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.
Which solution did I use previously and why did I switch?
We did not use a different solution for these use cases before InfluxDB.
How was the initial setup?
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.
What about the implementation team?
Four people were involved in the deployment process, and one person is now needed for maintenance.
What was our ROI?
We haven't gauged any measurable benefits; our company is more operational-focused.
What's my experience with pricing, setup cost, and licensing?
We use the open-source version of InfluxDB, so it is free.
Which other solutions did I evaluate?
We evaluated using PostgreSQL and a time-series database in Amazon, though I can't recall its name.
What other advice do I have?
InfluxDB works as expected with excellent scalability and stability, which is critical for our application. I rate InfluxDB ten out of ten overall.
Which deployment model are you using for this solution?
Hybrid Cloud
Deployment has been seamless with real-time data management capabilities and low latency performance
What is our primary use case?
We are developing a trading agent that uses multiple machine learning models to adapt to the crypto market in real time.
InfluxDB is used to collect data on crypto coin prices from exchanges like Binance and Bybit. Our use case requires low latency and the ability to query data effectively. We use
InfluxDB on a
DigitalOcean infrastructure in a containerized environment with
Docker.
What is most valuable?
The most important feature for us is low latency, which is crucial in building a high-performance engine for day trading. InfluxDB can handle around ten thousand messages per second, which is essential for our requirements. The solution's ability to store time series data is also significant in our crypto trading use case where time series data about prices is critical.
What needs improvement?
One area for improvement is the querying language. InfluxDB deprecated FluxQL, which was intuitive since developers are already familiar with standard querying. Though we can adapt to the
Flux language, I would like to see more development in this area and am unsure why FluxQL was deprecated.
For how long have I used the solution?
We have been using InfluxDB for the last eight months.
What was my experience with deployment of the solution?
We did not encounter any issues with the deployment. Using
Kubernetes allowed us to easily set up InfluxDB in a containerized environment. Although
DigitalOcean does not offer a managed database service, deploying our own container was straightforward and aligned with our continuous integration processes.
What do I think about the stability of the solution?
We have not experienced any stability issues with InfluxDB so far, and it has been acceptable for our needs.
What do I think about the scalability of the solution?
Scalability has not been an issue because we have only used one instance of InfluxDB. It is primarily used for real-time data acquisition rather than for extensive scaling.
How are customer service and support?
We have not needed to contact technical support. All resources required were available through documentation, enabling us to resolve any issues on our own.
How would you rate customer service and support?
Which solution did I use previously and why did I switch?
Previously, we used CassandraDB and
ScyllaDB, a fork of CassandraDB. While these were performant, they did not store data in the time series format essential for our needs. Once we discovered that there were databases like InfluxDB designed for time series data, we decided to try it.
How was the initial setup?
The initial setup was straightforward, as we used
Kubernetes to deploy InfluxDB. Although DigitalOcean does not offer a managed database service for InfluxDB, setting up our own container was an easy process.
What about the implementation team?
One person was responsible for the entire deployment of InfluxDB in our organization.
Which other solutions did I evaluate?
I have experience with CassandraDB and
ScyllaDB as alternatives.
What other advice do I have?
My advice for new users would be to ensure you are choosing the right engine for your domain. For InfluxDB, it performs well for low latency inputs and high-performance real-time data. While I would rate InfluxDB a ten on a scale of one to ten, users should be thoughtful about matching the engine to their specific needs.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Other
Handles serial data from sensors effectively and integrates well with third-party systems for visualization
What is our primary use case?
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.
What is most valuable?
The platform operates very quickly. It is easy to configure, connect, and query and integrates seamlessly with Grafana.
For how long have I used the solution?
I have been using InfluxDB for four years.
What do I think about the stability of the solution?
I have not experienced any stability issues with the product.
What do I think about the scalability of the solution?
Approximately 20% of our team uses InfluxDB.
What other advice do I have?
I recommend InfluxDB to others and rate it a ten.
Worked well for implementing the monitoring framework
What do you like best about the product?
We developed a centralized monitoring infrastructure to aggregate metrics from different source and influxdb worked well for the data integration from multiple sources for aggregation.
What do you dislike about the product?
There were not much direct plugins or integrations and we had to develop most of the out of box solutions.
What problems is the product solving and how is that benefiting you?
We analyzed few timeseries databases for the data integration and influxdb did satisfy all the data integration requirements and also the performance and pricing were as par compared to the others.
Best Db for High end usage
What do you like best about the product?
The influxdb is best in its performance and how it deals with a complex queries, resulting in a very faster response. The DB in performance is really great. This is one of the best Db.
What do you dislike about the product?
The documentation of DB is quite difficult to understand in the first time reading and implementation. There must be some good tutorial for different use cases.
What problems is the product solving and how is that benefiting you?
We used to have a streaming kind of the system in projects this influcxDB solves the problem of time stamp-based data that we can render easily and stitch and use. This also helped in analytics of readl time.
High Performant TimeSeries Database
What do you like best about the product?
Best TimeSeries & simple to understand and use, we can easily build efficient design with the simple DataTypes Fields & Keys.
Deciding it is key and rest will be taken care & it will be really fast.
What do you dislike about the product?
Memory Usage is something that is known problem,Query language limitations &Licensing
What problems is the product solving and how is that benefiting you?
Overall, InfluxDB's combination of speed, scalability, flexibility, and ease of use make it a popular choice for handling time-series data in a range of applications.
Easy to learn and use
What do you like best about the product?
I like that I could set up a Inlfux DB in a few hours and work with it.
What do you dislike about the product?
Nothing from what I experienced, but it could improve in their documentation.
What problems is the product solving and how is that benefiting you?
I used InfluxDB to make a time series database for a big project where I needed to store measurements from gas sensors.
Influxdb the easiest way to process time series data
What do you like best about the product?
The best thing is that Influxdb is an open-source tool that allows you to test time series projects for free. This is very useful for experiments and testing as many ideas as possible. Then if necessary, count with a payment method in the cloud that allows you to deploy the solution transparently. Nowing, the structure injecting data is very easy.
What do you dislike about the product?
The community and documentation are helpful, but it would be better if there were more information on the web and standard solutions with the best practices. Related to the ETL process is not as easy as in other languages. The dashboards are not complex as Grafana does.
What problems is the product solving and how is that benefiting you?
The way to inject data is ready to visualize and process.
Best solutions I've ever found to dealing with Timeseries coming from IoT devices
What do you like best about the product?
I like performances and query time, as well as the semplicity to being integrated into existing solutions. I purchased it through AWS, via Partner Catalog, and it was so easy!
What do you dislike about the product?
Dealing with scheduled operations and indexing is difficult due to the Timeseries definition.
What problems is the product solving and how is that benefiting you?
We managed to have real-time dashbording of our connected products storing 90 days of Timeseries data - always available - inside Influx.
