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.
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Tracking vessel movements seamlessly with continuous data collection and query execution
What is our primary use case?
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?
Neutral
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
does not work as expected
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.
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.
Best Time-series database
What do you like best about the product?
InfluxDB allows us to store large quantities of data in real-time that originate from our telemetry systems. Additionally, its simplicity and speed in performing backups using the provided tools ensure robust data security without additional complications.
What do you dislike about the product?
What I dislike about InfluxDB is the limited support and updates for older versions like 1.8, which are still widely used.
What problems is the product solving and how is that benefiting you?
InfluxDB solved our problem of storing the telemetry data from our prototypes and make it accesible to the rest of team. Also, allows us to querty the data in real time, simplifing our debug process.
An open-source database that can be used to insert data
What is our primary use case?
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.
What needs improvement?
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.
For how long have I used the solution?
I have been working with the product for five years.
What do I think about the scalability of the solution?
My company has 20-30 admins and 4,000-5,000 users. We have around 15,000 servers.
How are customer service and support?
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.
What's my experience with pricing, setup cost, and licensing?
The tool is an open-source product.
What other advice do I have?
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.
Navigating the Landscape of Time-Series Databases
What do you like best about the product?
InfluxDB stands out as a robust solution for time-series data management, providing a powerful and scalable foundation. Its emphasis on simplicity, integration capabilities, and monitoring features makes it well-suited for a variety of applications. While considerations exist, particularly for new users and in certain scenarios, the overall strengths of InfluxDB position it as a reliable choice in the landscape of time-series databases.
What do you dislike about the product?
Learning Curve for New Users:
While InfluxDB offers powerful capabilities, new users might encounter a learning curve, especially when mastering the specifics of InfluxQL and navigating the intricacies of the platform.
Clarity in Documentation:
The documentation, although comprehensive, could benefit from enhanced clarity in certain sections. Improvements in this area would contribute to a more user-friendly onboarding process.
Complexity in High-Cardinality Scenarios:
In scenarios with high cardinality, complexities may arise, necessitating careful consideration and optimization to ensure optimal performance.
While InfluxDB offers powerful capabilities, new users might encounter a learning curve, especially when mastering the specifics of InfluxQL and navigating the intricacies of the platform.
Clarity in Documentation:
The documentation, although comprehensive, could benefit from enhanced clarity in certain sections. Improvements in this area would contribute to a more user-friendly onboarding process.
Complexity in High-Cardinality Scenarios:
In scenarios with high cardinality, complexities may arise, necessitating careful consideration and optimization to ensure optimal performance.
What problems is the product solving and how is that benefiting you?
InfluxDB's capabilities address critical pain points related to time-series data, offering efficient solutions that benefit users by ensuring optimal performance, scalability, simplified querying, proactive issue resolution, and versatile integration possibilities.
Efficiently customize alerts, data visualization, but lacks in stability
What is our primary use case?
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.
What is most valuable?
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.
What needs improvement?
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.
For how long have I used the solution?
I used this solution for one and a half years.
What do I think about the stability of the solution?
I would rate stability at seven. We faced two to three incidents where we lost data.
What do I think about the scalability of the solution?
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.
How are customer service and support?
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.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
I use Datadog, New Relic, Grafana and Prometheus. I switched to Influx DB because of its user interface.
How was the initial setup?
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.
What's my experience with pricing, setup cost, and licensing?
InfluxDB recently increased its price. It is very expensive now. It is now per month; earlier, it was per year-based license.
What other advice do I have?
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.
Which deployment model are you using for this solution?
Hybrid Cloud
Problem solving DB
What do you like best about the product?
This DB supports multiple use cases and solves them perfectly. Like support for IOT and accurate like analytics, and how can I forget support for Gaming
What do you dislike about the product?
A slight learning curve bugs me; apart from that, it's perfect. The issue I faced can be my problem, but I'd like to mention it.
What problems is the product solving and how is that benefiting you?
Problems were many, but I would shed light on some crucial ones. Integration is relatively easy and supports widely accepted languages. I implemented it in c#. A single DB solved my analytical, reporting and DevOps issues.
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.
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