An Introduction to InfluxDB

When it comes to end user data, metrics, and management, every second counts. Real-time cloud solutions for all infrastructure monitoring don’t always deliver information in a timely manner. Maintaining high availability is the goal. On top of data availability, maintenance, and initial setup times can be daunting to the bottom line. The ideal solution must collect and store metrics and analytical data and can be accessed at anytime with real-time information that offers hassle free start-up solutions without the need for constant updating and maintenance.

As a developer, I’m looking for a real-time solution to capture and analyze time-series data to enhance customer experiences for my applications and services. I heard that InfluxDB can capture the information I need and store it in an API where I can access it in real-time with low maintenance and an immediate initial startup. Is InfluxDB the analytical solution that I need to sustain and enhance my application to the satisfactory level of my end users?

InfluxDB is an open source time-series database written in Go. Time-series data includes server performance metrics, financial averages overtime, and sensor data. This sensor data typically includes temperature, barometric pressure, wind speeds, and other data that can be measured by a sensor. The database includes APIs for storing, querying, and processing data. Some other features include ETL monitoring and alerting, user dashboards, and visualizing and exploring the data. If you’re planning on using it for custom monitoring, metrics collections, real-time analytics plus IoT and sensor data workloads, then InfluxDB is perfect for you. In fact, the Influx database was built as a sustainable solution for storing and querying large volumes of time-series data.

InfluxDB is great for developers building DevOps monitoring (Infrastructure, application and cloud monitoring), IoT Monitoring, and Real-Time Analytics applications. InfluxDB is known for having out-of-the-box support for mathematical and statistical functions across time-ranges. 

The best part about using the influxdb database is that it is ready-to-use for time series workloads without additional configuration. The only learning you must do is basic InfluxQL, which is nominal in comparison to other database systems with the same promise. InfluxQL enables you to write human-friendly queries which will be interpreted by the Influx servers. InfluxDB also allows you to run ad-hoc queries without the need for additional engineering time. When it comes to maintenance, InfluxDB requires no support systems to be fully functional. 

You can use the InfluxDB in both small and large-scale businesses. The database has the ability to downsample and retain raw data at your discretion to save space. You can choose which data you would like to compact and which raw data you would like to keep for as long as you’d like. This will save you money and space on your servers because you can summarize your information and save the summaries in raw format to consistently keep track of your data while compressing larger unnecessary data files. The downsampling can be done when files reach a specific age so that your database will always be current.

Finding the right solution for your end users’ needs is hard, but when it comes to databases, there isn’t really one that can compare to InfluxDB. You’ll be ready to use the database right out-of-the-box or on the onset of downloading. Because there is no maintenance required for the database, you can run the database interruption-free. There’s nothing better than knowing that your information is safe on your API and that you have access to all of your metrics and data in real-time. There is no doubt about it, InfluxDB is the best time-series database out right now!

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