Overview
What is InfluxDB?
The InfluxDB is a time series database from InfluxData headquartered in San Francisco. As an observability solution, it is designed to provide real-time visibility into stacks, sensors and systems. It is available open source, via the Cloud as a DBaaS…
Great time series database
InfluxDB is a solid time series database
InfluxDB is the real deal for time series!
Perfect for storing time-series data
Product Demos
Node.js metrics demo in Play with Docker (using InfluxDB & Grafana)
Demo Ansible Playbook | InfluxDB + Telegraf + Grafana
Performance Testing Solution K6 & Integration with InfluxDB, Grafana and Jenkins.
InfluxDB Clustering, Monitoring and Data Exploration Demo - June 2016
InfluxDB Clustering, Monitoring and Data Exploration Demo
InfluxDB CLI Demo
Product Details
- About
- Tech Details
What is InfluxDB?
InfluxDB Video
InfluxDB Technical Details
Operating Systems | Unspecified |
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Mobile Application | No |
Comparisons
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Reviews and Ratings
(16)Community Insights
- Business Problems Solved
- Pros
- Cons
- Recommendations
Users have found the integrated Dashboards in Influx highly beneficial for monitoring and visualizing critical data. They appreciate the software's effectiveness in time series data analysis and alerting on threshold changes. Influx has successfully been utilized by users to collect and visualize real-time data series from sensors and applications. The holistic view provided by the Influx user interface allows users to effectively monitor the performance of their applications during testing. Leveraging the Infux DB dashboard, users can easily monitor various utilization metrics across their instances, such as response time, throughput, CPU, memory, disk, and network. Additionally, the software provides convenient alerting capabilities to notify relevant parties for necessary actions.
Users have seamlessly integrated Influx with their applications and are impressed with the one-stop web page for monitoring upgrades. The software proves to be effective for collecting and monitoring data from batches, enabling users to easily track running time and compare results. Furthermore, Influx has successfully addressed challenges related to data availability and robust data transfers with minimal lag. Users have leveraged the software for bandwidth consumption optimization, data modeling using time series forecasting, and real-time data processing or monitoring. In terms of query performance, Influx excels particularly when time is the main parameter. Users have harnessed the power of InfluxDB to store telemetry information from thousands of machines and utilize this valuable information for monitoring and reporting purposes.
High Availability and Scalability: Many users appreciate the high availability and scalability of InfluxDB, making it suitable for handling large amounts of data. Several reviewers have mentioned that they can rely on InfluxDB to efficiently handle their data needs, allowing them to scale their applications without worrying about performance issues.
Real-time Performance: The real-time performance of InfluxDB is impressive, with fast query execution times and low latency. Numerous users have praised its ability to provide quick insights and analysis on real-time data. This makes it an ideal choice for tasks such as real-time monitoring and data analysis.
Ease of Use in Querying and Processing Data: Users find one of the key strengths of InfluxDB lies in its ease of use when querying, filtering, and processing data. They appreciate the built-in data explorer, dashboard building capabilities, and alert mechanisms that simplify these tasks. Several reviewers have expressed their satisfaction with how intuitive it is to work with InfluxDB's interface for data manipulation.
Difficult Learning Curve: Some users have mentioned a slight learning curve when using the TICK stack components, particularly with understanding the query language used in InfluxDB. They acknowledged that it could be their own problem but still found it challenging to grasp the concepts and syntax of the language.
Lack of Direct Plugins/Integrations: Several users have expressed dissatisfaction with the lack of direct plugins or integrations available for InfluxDB. They stated that they had to develop most of the out-of-box solutions themselves, which added extra effort and time to their implementation process.
Documentation and Tutorial Difficulties: Users have found the documentation of the database difficult to understand and suggested the need for better tutorials. They also mentioned that InfluxDB's documentation could be improved overall, as it was not always clear and comprehensive enough to provide effective guidance for beginners.
Users have recommended using InfluxDB for a variety of use cases due to its remarkable data storage and querying abilities. It is also suggested for fast and efficient data visualization, especially for enterprise organizations. Additionally, users advise starting with a small on-premise setup when implementing InfluxDB and then deciding between on-premise and cloud-based solutions as usage grows to achieve the lowest cost implementation. These recommendations highlight the versatility, performance, and cost-effectiveness of InfluxDB as a time series database solution.
Attribute Ratings
Reviews
(1-4 of 4)Great time series database
- Perfect handling telemetry data.
- Low latency, near real time.
- SQL-like language makes it easier to query.
- Query return can sometime out of order.
- Some operations can be hard to execute, like delete function.
- Have to be aware of timely order to have a good performance.
- Provided us a time series DB.
- With the SQL-like language, it is very easy to learn.
- Empowered us to keep track of our events.
InfluxDB is a solid time series database
- Time series data
- Very fast queries
- Many options to configure and tune database
- GUI based administrator console
- Help accelerate problem resolution time
InfluxDB is the real deal for time series!
- Scalability - InfluxDB scales so well and even lets you create a database cluster without needing a database administrator.
- Data Reduction - InfluxDB's primary use case is to allow the data to be input at any interval or speed regardless of the volume of data. The way this is later queried is by reducing the data based on the input data.
- Quick start - Unlike other monolithic time series database it can easiliy startup with just a few minutes of reading their documentation
- Cloud Native - This database engine is made to operate in Docker & cloud first!
- Small, but growing community - This database engine's community is much smaller than alternatives. This can make finding a DBA or support less easy, but not impossible.
- Documentation could be improved - The docs for getting started don't effectively lead first-time users to understand how the underlying systems are designed.
- Performance Analysis - There seems to be a lack of tools to give context to slow queries or other performance issues
- Out-of-the-box security - The out of the box security is designed to operate in an internal network and is limited.
I would NOT recommend InfluxDB for any non-time-based data.
- No financial costs for internal dev team - as we have an engineering team we do not have any financial expenses in using InfluxDB
- Time to implement was minimal
- InfluxDB has not required any substantial upkeep or operations time to use
Perfect for storing time-series data
Since InfluxDB is widely spread, many other software products offer some sort of integration (such as Grafana). Therefore, metrics graphs based on InfluxDB data are often embedded into other software products which are being used by my customers.
This solves the problem that customers often have to get used to different graphical interfaces when viewing common monitoring data and performance metrics. But since graphs (based on InfluxDB data) can get embedded into main GUIs, customers only need to login into one interface and have a complete overview of their data.
InfluxDB itself solves another problem. In the past, many companies used MySQL-like products to store time-series data. This was highly inefficient and difficult to manage. With InfluxDB, many issues those customers had disappeared.
- Storing time-series data
- Providing time-series data over an HTTPS API
- Accepting new data inputs through the same HTTPS API
- Providing existing data sets in a very fast and efficient manner
- The open source version does not have ACLs, which is crucial for enterprise customers
- The open source version has no high availability or clustering option, even the enterprise edition is limited in this way
- The open source and the enterprise versions both have no read load-balancing systems (sharding is possible, though)
- Backup and recovery can only be performed for all data sets, not for subsets
- InfluxDB is a quick and easy solution if the customers need to store and handle large amounts of time-series data
- InfluxDB is so simple that almost no training is needed
- InfluxDB had a negative impact in terms of security since the open-source version lacks relevant features; therefore all customers have to build their own security solution on top of InfluxDB if they can't afford the enterprise version
- Storing metrics
- Storing performance data
- Providing the data for beautiful visualizations
- InfluxDB can be combined with Grafana to generate beautiful graphs
- InfluxDB in combination with InfluxDB relay can achieve a "poor man's" HA setup
- InfluxDB can be used together with AI for providing additional value for monitoring environments
- Since InfluxDB only provides one main feature, there won't be any surprises.