InfluxDB Reviews

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.

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.

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.

We have been using InfluxDB for the last eight months.

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.

We have not experienced any stability issues with InfluxDB so far, and it has been acceptable for our needs.

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.

We have not needed to contact technical support. All resources required were available through documentation, enabling us to resolve any issues on our own.

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.

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.

One person was responsible for the entire deployment of InfluxDB in our organization.

I have experience with CassandraDB and ScyllaDB as alternatives.

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.

Public Cloud

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.

Our usage of Influx is very specific. We use it for our casino stack and applications. We use it for monitoring, logging, and metrics and trend analysis for player wagering. It is for casino data. We correlate all that data and generate reports for data warehousing. So, we use it massively in our stack for the casino for a lot of things. 

We haven't yet migrated to Influx 2.0. We are still using Influx 1.8 because we have multiple workloads in production. It is going to take some time, and we need to ensure that the latest one is stable and the framework also brings a lot of different languages.

We use it on-premise and in the cloud. We have both. It is a private cloud on AWS.

In our case, it started with a necessity to fill the gap that we had in monitoring. We had very reactive monitoring without trend analysis and without some advanced features. We were able to implement them by using a time series database. We are able to have all the data from applications, logs, and systems, and we can use a simple query language to correlate all the data and make things happen, especially with monitoring. We could more proactively monitor our systems and our players' trends.

We can integrate it with everything. It has an API. We can put any data there. We are developing apps. We are creating scripts. We are doing lots of things. There are different ways to configure it. As a database, it just has to ensure that data is there, and it is properly stored with the tags, fields, measurement names, and time stamps. The focus is that the data that you put in there is perfectly stored. 

I use Kapacitor a lot. It is the feature that allows us to create batch jobs and interact with the data that we have. That's the most interesting feature. 

The query language is very similar to SQL, which is very useful because most of us have a background in SQL language.

They have the Telegraf agent that gets the data and puts it in Influx. We can also put data into Influx through the API. We are doing a lot of custom-based agents and a lot of scripts that are adding data to Influx. As a time series database, it is very powerful and lightweight. It can deal with heavy workloads very easily. That, for me, is the main advantage of Influx as compared to other databases. 

Influx has TICK Stack, which contains multiple services and multiple products that work together. InfluxDB is just a time series database, and it works really well. I haven't yet had the time to look into the new stack based on Influx 2.0, but currently, as a time series database, InfluxDB is working the way it is supposed to work. 

In terms of features that I would like to see or have, in the community version, some features are not available. I would like to have clustering and authentication in the community version. 

I would also like to have high availability features, such as replication, active-active, etc. If they can put an extra plugin or service on top of it, it would be something interesting. I am not sure if they have high availability to make it data center-aware for clustering. For example, I am not sure whether you can have it at different locations with big clusters that are location-aware. Even in their documentation or presentation, they talk too little about high availability and extended clusters with different locations. They might already have it in the newer versions. We have Influx 1.8 in our production in the stage and internal workloads environments. 

The other products in their ecosystem, such as Chronograf, can be improved. Chronograf is a dashboarding or visualization layer product, and that, for sure, can be improved.

I have been using this for five years.

I really like it. I always recommend the stack to lots of friends I have in other places. It is really good, and it helped us a lot.

We will see scalability with the new version. In terms of its users, everything is automated. So, there are almost zero users. Admins and DevOps are the only ones that go to Influx to manage or implement any kind of tweaks, improvements, or developments, but it touches almost everyone, which includes managers who do reports regarding the business, data warehousing, our 24/7 teams for monitoring, developers, and system administrators. They go to Grafana, and they have all the dashboards for system availability and everything else. It touches almost everyone.

It is being used extensively. As the business grows and we create a new environment, a huge part of the management of that environment comes from Influx. It is one of the primary stacks that we build for monitoring and reporting. Because everything is in Influx, it always comes first.

I did a search and used the community forums and help, but I never had to contact them. Their community is really big, helpful, and active. It is very easy to just go to their support site and search for solutions or ask questions. That's another thing where they are very good.

We mainly went from Icinga. It is like Nagios. So, we were using Nagios monitoring, but because the monitoring was so reactive, we wanted something new that could help us with the business requirements. We needed something that could host the metrics and data from multiple sources and can be used to correlate. It was because of the necessity we moved away from Nagios, which is very focused on systems monitoring, to something that uses a time series database and has a simple SQL query language that we can use to correlate data and create trends.

We implemented everything. The setup is straightforward. There is a learning curve, but the setup is very easy. They have repositories for most distributions. You just have to install from a binary, and the entire stack of Influx is up and running. For most operating systems, they already have repositories that allow you to just install it with one command. I would rate it a ten out of ten in terms of ease of setup. 

In terms of duration, deploying InfluxDB took minutes. It is like installing an app on your laptop. It is very easy and quick to deploy InfluxDB, but deploying what we have has been an ongoing process for the last five years.

I implemented it myself. In terms of maintenance, it is very lightweight. We just ensure that Influx doesn't get any updates other than the security updates that are always coming from the repository. It is very simple to maintain and update.

I went straight to Influx. I came across Influx, and I tried it, tested it, and learned a little bit more about it. I saw that this would do what we needed and meet our requirements.

It depends a lot on what you are going to use it for but just enjoy it. It is very powerful. I would advise learning the TICKscript language. I know that the latest Influx 2.0 is using a different language than Influx SQL, but I would advise learning how to develop using their framework. You will see how powerful it is to use for a big data cluster. So, explore the batch processing and the scripting language that they have in 2.0. We use TICKscript, which is very powerful and allows you to do everything you need.

I would rate it an eight out of ten.

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.

Hybrid Cloud

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.

Hybrid Cloud

Amazon Web Services (AWS)

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. 

I'm using InfluxDB to store documents related to the database and to populate data through their funnel.

The most valuable feature of the solution is we can use InfluxDB to integrate with and plug into any other tools.

The solution's UI can be more user-friendly.

I would like to have better more detailed documentation on how to integrate the solution with other tools.

I have been using the solution for three years.

I have no issues with the stability of the solution.

I have multiple projects that I am using for InfluxDB, so it is scalable. The solution is very scalable and very easy to use.

The initial setup is straightforward. As a first-time user, the deployment usually takes us half an hour to understand all the requirements. After that, we can install the solution in one to two hours, which is efficient for installing on the client side.

I give the solution a seven out of ten. The monitor is easy to use and integrate. Integration with the tools is very easy, which is why it is comfortable to test and monitor the tools that are connected to InfluxDB. we can then see the results of our monitoring.

We have over 50 people in our organization using InfluxDB and over 500 people testing.

We are using InfluxDB because it is easy to use and in my time, it has helped in live monitoring of the log testing.

For first-time users of the solution, it can be difficult to learn how to write custom data and classify it for monitoring purposes. There are many builder models in the market that can be implemented and used, but if we want to write our own, using InfluxDB can be difficult.

On-premises

I use InfluxDB for querying based on time ranges and window operations.

InfluxDB's best feature is that it's a cloud offering. Other good features include its time-series DB, fast time-bulk queries, and window operations.

InfluxDB cannot be used for high-cardinality data. It's also difficult and time-consuming to write queries, and there are some issues with bulk API. 

I've been using InfluxDB for a year.

InfluxDB is stable.

InfluxDB is scalable, but if you want to scale it on an enterprise level, you'll have to spend lots of money on licenses.

The initial setup is easy, but it takes time at first to understand and set up InfluxDB.

InfluxDB is open-source, but there are additional costs for scaling.

I recommend going with the cloud version of InfluxDB, as it's very cheap and effective. InfluxDB is very powerful, but it requires some technical skill and can't be used by just anyone. I would rate InfluxDB seven out of ten.

Public Cloud

Amazon Web Services (AWS)