InfluxDB

Sensors that collect sci­en­tif­ic or in­dus­tri­al mea­sure­ment data generate large volumes of data in a short period time. This data has to be processed together with a timestamp of the mea­sure­ment. Special databases are required for this time series data. This article focuses on InfluxDB, a database man­age­ment system (DBMS) specially designed for this task.

InfluxDB is a database man­age­ment system developed by In­flux­Da­ta, Inc. InfluxDB is open-source and can be used free of charge. The InfluxDB En­ter­prise version offers main­te­nance agree­ments and special access controls for business customers, and is installed on a server within a corporate network. In addition, the new InfluxDB 2.0 version runs as a cus­tomiz­able cloud service with a web-based user interface for data ingestion and vi­su­al­iza­tion.

The InfluxDB database man­age­ment system is written in Google’s pro­gram­ming language Go, also known as Golang. The first version of InfluxDB used InfluxQL, a query language developed by In­flux­Da­ta, for external database queries.

InfluxDB 2.0 is written in a new language called Flux, which In­flux­Da­ta publishes on GitHub as an open-source project. The project is updated on GitHub by de­vel­op­ers working with time series data. Flux is a stand­alone language for time series databases (TSDB). It can be used with InfluxDB version 1.7 and higher, either in­de­pen­dent­ly or with third-party databases.

Flux is optimized for ETL processes (extract, transform, load) in databases and is not com­pat­i­ble with the InfluxQL query language pre­vi­ous­ly used. However, In­flux­Da­ta is planning a migration path for existing customers to translate InfluxQL code into Flux.

Flux syntax is based on the popular language JavaScript. It is easy to learn and can be expanded. A key feature of Flux is that it can integrate different data sources using third-party APIs, for example. As a result, Flux is com­pat­i­ble with analytics tools like Jupyter. The Apache Arrow data in­ter­change interface permits com­mu­ni­ca­tion with other systems and in­te­gra­tion in big data en­vi­ron­ments.

InfluxDB is ideal for time-series databases (TSDB), which store time series. These databases are used, among other things, to store and analyze sensor data or protocols with time­stamps over a certain period of time. For example, Internet of Things devices or sci­en­tif­ic measuring in­stru­ments deliver millions of incoming data sets in a constant stream of data.

This data must be quickly processed once it reaches the database. For this reason, InfluxDB includes a built-in time service that uses the Network Time Protocol (NTP) to ensure that time is syn­chro­nized between all systems.

With InfluxDB, a database can be very compact and must contain only two or three columns. In this example, the data source, the actual value and the cor­re­spond­ing time stamp are stored in the database.

InfluxDB dif­fer­en­ti­ates between tag and field columns. Where a tag is simply metadata that is included in the index, fields contain values that can be analyzed. In our example, the first column is a tag and the second one is a field. This dif­fer­en­ti­a­tion makes it easier to manage the database and analyze mea­sure­ment data.

Compared to ordinary re­la­tion­al databases, TSDBs like InfluxDB offer clear speed ad­van­tages when it comes to storing and pro­cess­ing time-stamped mea­sure­ment data. A tra­di­tion­al DBMS slows down when or­ga­niz­ing complex indexes, which are not used at all in this area of ap­pli­ca­tion. InfluxDB can maintain high write speeds over a long period of time because it uses a very simple index.

Unlike version 1.x, the new InfluxDB Cloud 2.0 from In­flux­Da­ta is a cloud-based solution that can run on Amazon Web Services (AWS), the Google Cloud Platform (GCP) or Microsoft Azure. With server­less computing, you don’t need your own server in­fra­struc­ture. In the cloud version, you no longer have to reserve in­di­vid­ual servers. Instead, the system au­to­mat­i­cal­ly adjusts to the load, which is important for in­dus­tri­al IoT ap­pli­ca­tions and machine learning, where the volume of data can change in­stan­ta­neous­ly.

Whereas the first version required the TICK stack (Telegraf, InfluxDB, Chrono­graf and Kapacitor), InfluxDB 2.0 already has every­thing you need. Both the local and cloud versions contain the entire database man­age­ment system in a single program file currently available for 64-bit Linux, Linux for ARM proces­sors, macOS, and as a docker container. Telegraf etc. can still be used to collect data for InfluxDB 2.0.

You can create Telegraf con­fig­u­ra­tions in­ter­ac­tive­ly or copy existing con­fig­u­ra­tions to send data to the InfluxDB Cloud 2.0 instance. Once you’ve con­fig­ured InfluxDB cloud to collect data, you can create personal dash­boards to query and display the data.

In the InfluxDB data explorer, you can explore and visualize the collected data. You can adjust time intervals and ranges for re­fresh­ing the dashboard’s data according to the needs of your project. The InfluxDB user interface provides a variety of at­trac­tive vi­su­al­iza­tion options. The web in­ter­faces allows you to move seam­less­ly between the Flux Builder and manual editing of database queries.

On the “Usage” page, you can view your current database usage at any time to determine whether a paid plan might be worth­while.

Free plan (with limits): No down­load­ing, no in­stal­la­tion and no in-house server in­fra­struc­ture required; fastest in­tro­duc­tion to InfluxDB 2.0 tech­nol­o­gy; the free plan is designed for getting started with InfluxDB and for small hobby projects.

Flux support: Flux is a stand­alone scripting and query language for time series databases that increases pro­duc­tiv­i­ty by allowing easy reuse of code. Flux was developed and optimized for working with data in InfluxDB 2.0, but it can also be used with other data sources.

Unified API: The unified InfluxDB v2 API offers access to all InfluxDB com­po­nents, such as data ingestion, query, storage and vi­su­al­iza­tion. This enables seamless movement between the installed open source version and the InfluxDB Cloud 2.0 version.

Vi­su­al­iza­tion and dash­boards: Based on the in­no­v­a­tive Chrono­graf project from the first version of InfluxDB, the new user interface offers sig­nif­i­cant­ly faster results when vi­su­al­iz­ing and querying data in real-time.

Usage based pricing plans: Usage-based billing offers more flex­i­bil­i­ty than a self-hosted database system and ensures that you only pay for what you actually use.