#influxdb

InfluxDB – designed specifically for time series. Insanely fast writing, automatic compression, and native support for Grafana visualization. Best fit if you need to process huge amounts of raw telemetry data without relational requirements.

TimescaleDB – PostgreSQL enhanced with full time-series capabilities. Full SQL support, joins, and Postgres ecosystem integration. The best choice once your asset-related information needs to connect with metadata or maintenance schedules.

Time-series pipelines for asset tracking? TimescaleDB. Raw telemetry streams at extreme scale? InfluxDB.

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Case Details

With the rapid development of smart manufacturing, factory automation and data-driven management have become key aspects of improving production efficiency, ensuring quality, and achieving refined management. Traditional production monitoring systems often rely on expensive hardware and complex system architectures. However, modern solutions are moving towards low-cost, high-efficiency directions. The combination of the ARM Architecture Industrial Gateway BL340 and InfluxDB provides an efficient, flexible, and easy-to-deploy solution for factory data monitoring and logging, helping companies achieve accurate data collection, storage, and auditing of production processes.

Overview of the BL340 Industrial Gateway

The BL340 is an ARM Architecture Industrial Gateway widely used in industrial automation, data acquisition, edge computing, and other fields. Its powerful processing capabilities, low power consumption, and compact size make it an ideal solution for use in factory environments. The BL340 features multiple interfaces for seamless connection with on-site sensors, PLCs, and devices, enabling the real-time acquisition of critical production data and initial processing before transmission.

InfluxDB — A Database Designed for Time-Series Data

InfluxDB is an open-source time-series database specifically designed for efficiently storing and querying time-stamped data. In production monitoring systems, many data types are time-sensitive, such as temperature, humidity, pressure, and flow rate. InfluxDB’s high-performance write and query capabilities make it an ideal choice for factory data logging and analysis. It can store and process large volumes of data quickly, supporting multi-dimensional queries and analysis, ensuring data availability and reliability.

Integration of BL340 with InfluxDB

Combining the BL340 industrial gateway with InfluxDB allows users to leverage the strengths of both technologies, enabling efficient and accurate data collection and logging of production processes.

Real-Time Data Acquisition and Processing

The BL340 can connect to various devices and sensors in the factory using protocols like Modbus, OPC, and MQTT to collect production data in real-time. After processing the data locally, the BL340 transmits it to the InfluxDB database for storage. During this process, the BL340 not only acts as a data collector but also performs preprocessing tasks such as data cleaning, anomaly detection, and calculation to ensure the accuracy of the data.

Efficient Data Storage and Querying

InfluxDB is optimized for handling time-series data. Each data entry has a timestamp, and InfluxDB can efficiently store vast amounts of historical data. Users can flexibly query data based on various criteria, such as time range or device/sensor dimensions. For real-time production monitoring and historical data analysis, InfluxDB offers fast query responses and accuracy, ensuring that the system remains responsive under heavy data loads.

Data Auditing and Traceability

Recording production data is critical for auditing and regulatory compliance. In industries such as food and pharmaceuticals, every step of the production process must be meticulously recorded for later review. By utilizing InfluxDB’s timestamp feature and the stability of the BL340, production data can be continuously and fully logged, meeting auditing requirements. Each data point is traceable to a specific production step, ensuring full transparency of the process.

Visualization and Alerts

By integrating InfluxDB with visualization tools like Grafana, companies can achieve real-time display and analysis of production data. Grafana supports various visualization methods, such as charts and dashboards, helping managers and engineers monitor production data in real-time and identify potential issues. Additionally, alert rules can be set up to trigger notifications when data anomalies occur, ensuring timely intervention and preventing production interruptions or quality problems.

Production Data Logging: Auditing and Managing Key Data

In a production environment, logging key data is essential not only for optimizing production efficiency but also for ensuring compliance and traceability. The combination of the BL340 and InfluxDB enables the following functionalities:

Automated Data Collection: Data is automatically collected from key production stages, such as equipment status, production speed, temperature, and humidity, without manual intervention.

Precise Timestamping: InfluxDB provides accurate timestamps for each data entry, ensuring the timeliness and accuracy of the data and facilitating post-production auditing and traceability.

Data Integrity: The BL340 and InfluxDB integration ensures reliable data storage, preventing data loss, and allowing for easy backup and recovery.

Compliance Assurance: By continuously logging production data, factories can easily meet quality inspections, compliance audits, and other regulatory requirements, ensuring that the production process meets industry standards.

Application Example

Consider an automotive manufacturing plant where temperature, humidity, pressure, and other data need to be monitored in real-time. By installing sensors at critical points along the production line, the ARM Architecture Industrial Gateway BL340 can collect this data and transmit it in real-time to the InfluxDB database. Managers can use Grafana to monitor this data in real-time and receive alerts in case of abnormalities. Thanks to InfluxDB's powerful query capabilities, managers can trace every data point back to its corresponding production step, facilitating auditing and troubleshooting.

Conclusion

The combination of the ARM Architecture Industrial Gateway BL340 and InfluxDB provides an efficient and flexible solution for production data logging and monitoring in factories. The BL340 offers powerful data acquisition and processing capabilities, while InfluxDB enables high-performance time-series data storage and querying. Whether for data auditing, production optimization, or equipment failure prediction, this solution provides robust support, helping companies enhance production efficiency, ensure quality, and reduce costs.

Case DetailsUnder the general trend of Industry 4.0 and intelligent manufacturing, it is crucial to collect, store, analyze and visualize all kinds of data in the production process in real time. This helps enterprises better understand the production status, optimize the process flow, predict equipment failures and ultimately improve production efficiency and reduce operating costs.

Traditional industrial data collection and visualization solutions often rely on expensive PLC, SCADA systems and host computer software, which is a considerable burden for small and medium-sized enterprises or cost-sensitive application scenarios. In recent years, with the maturity of ARM technology and the prosperity of the open source software ecosystem, a more cost-effective and flexible solution has gradually attracted attention: an industrial data collection and visualization system based on ARM industrial computers and Grafana.

Why choose ARM industrial computers?

ARM architecture processors are widely used in the embedded field due to their low power consumption, low cost and small size. Applying them to industrial computers brings the following advantages:

Low power consumption and fanless design: Suitable for industrial environments with high requirements for power consumption and heat dissipation, reducing energy consumption and maintenance costs.

Cost-effectiveness: Compared with traditional x86 architecture industrial computers, ARM industrial computers usually have lower hardware costs, which lowers the threshold for overall system deployment.

Small size: Easy to integrate into various industrial equipment and control cabinets, saving space.

Rich interfaces: Many ARM industrial computers are equipped with common industrial interfaces such as GPIO, RS-232/485, Ethernet, etc., which are convenient for connecting various sensors and devices.

Good software compatibility: With the wide support of open source operating systems such as Linux, the software ecosystem on the ARM platform is also becoming more and more perfect, providing rich options for data collection and visualization.

Why choose Grafana?

Grafana is an open source data visualization and monitoring platform. With its powerful functions and ease of use, it is becoming more and more popular in the industrial field:

Powerful data source support: Grafana supports various mainstream databases (such as InfluxDB, TimescaleDB, PostgreSQL, MySQL, etc.), time series databases, and third-party APIs, which can easily connect and query industrial data from different sources. Rich visualization panels: Provides various chart types (line charts, bar charts, pie charts, dashboards, heat maps, etc.) and plug-ins, and users can create intuitive and easy-to-understand industrial data visualization dashboards according to their needs. Flexible alarm function: According to the set thresholds and rules, key industrial data can be monitored and alarmed in real time, and abnormal situations can be discovered and handled in time. Easy to install and configure: The installation and configuration process of Grafana is relatively simple, and it has complete documentation and community support. Cross-platform compatibility: Grafana can run on a variety of operating systems and hardware platforms, including ARM architecture industrial computers. Strong scalability: Supports plug-in extensions, and users can add new data sources, panels, and alarm methods according to specific needs. User-friendly interface: Provides an intuitive web interface for users to easily create, edit and manage dashboards.

Application scenarios of ARM industrial computers with Grafana

The solution of ARM industrial computers with Grafana is suitable for various scenarios that require industrial data collection and visualization, such as:

Equipment status monitoring: Real-time monitoring of the operating status of industrial equipment (such as temperature, pressure, current, speed, etc.), timely detection of abnormalities, prediction of equipment failures, and improvement of equipment utilization.

Production process monitoring: Monitor the key parameters of the production line (such as output, yield, energy consumption, etc.) to help optimize the production process and improve production efficiency.

Environmental parameter monitoring: Monitor temperature, humidity, PM2.5 and other parameters in the industrial environment to provide a good environment for production.

Energy management: Real-time monitoring of the factory's energy consumption (such as electricity, water, gas, etc.) to help enterprises optimize energy and control costs.

Remote equipment monitoring: Through the network connection, ARM industrial computers deployed in different locations can be used to realize centralized monitoring and management of remote equipment.

Small automation system: For some cost-sensitive small automation projects, ARM industrial computers can be used as the core of data collection and control, and Grafana can be used for visualization.

Steps to build an ARM industrial computer and Grafana system

To build an industrial data collection and visualization system based on ARM industrial computers and Grafana, the following steps are usually required:

Choose a suitable ARM industrial computer: Choose an ARM industrial computer with sufficient processing power, memory, storage space and required industrial interfaces according to the needs of the application scenario.

Install the operating system: Install Linux or other operating systems that support Grafana on the ARM industrial computer.

Install data acquisition software: Select appropriate data acquisition software or write a custom data acquisition program based on the type of data and device interface to be collected. Common data acquisition solutions include:

Protocol drivers such as Modbus/OPC UA: Used to communicate with PLCs, sensors and other devices.

Tools such as Node-RED/Python: Used to build flexible data collection and processing processes.

Message queues such as MQTT: Used to receive real-time data from various sensors and devices.

Install and configure the database: Select a suitable time series database (such as InfluxDB, TimescaleDB) or other database to store the collected industrial data.

Install Grafana: Install Grafana on the ARM industrial computer. Usually it can be installed through the package manager or by downloading the installation package.

Configure data source: Add the configured database as a data source in Grafana.

Create and customize dashboards: Use the various panels and chart types provided by Grafana to create intuitive industrial data visualization dashboards according to needs.

Configure alarm rules (optional): Set alarm rules based on key indicators and send notifications when data exceeds the preset threshold.

Deployment and testing: Deploy the system to an actual industrial environment for testing and verification. 

Advantages

Case Details

ARMxy Based Single Board Computer have been widely used in the field of Internet of Things (IoT) due to their low power consumption, high performance, and cost-effectiveness. As an open source time series database, InfluxDB performs well in storing and analyzing the massive time series data generated by IoT. Combining the two can build an efficient and reliable IoT data platform.

Advantages of ARMxy Based Single Board Computer in the IoT field

Low power consumption: ARM architecture has lower power consumption and can run 7*24 hours a day, stable and low power consumption

High performance: It can process a large amount of sensor data in real time to meet the real-time requirements of IoT.

Cost-effectiveness: Compared with industrial computers with x86 architecture, it has lower cost and reduces deployment costs.

Miniaturization: It has a small appearance and is suitable for deployment in a small space.

Advantages of InfluxDB in IoT data storage and analysis

High-performance writing: Ability to efficiently write large amounts of time series data.

Flexible data model: Supports multiple data types and tags, and can flexibly store various IoT data.

Powerful query function: Provides a rich query language that can perform complex analysis on time series data.

High availability: Supports cluster deployment to improve system reliability.

Typical application scenarios of ARM Edge Computer with InfluxDB

Industrial IoT: Collect various sensor data of production equipment, conduct real-time monitoring and analysis, and optimize the production process.

Smart home: Collect the operating status data of home devices to realize the automatic control of smart home.

Environmental monitoring: Collect environmental sensor data, monitor environmental quality, and achieve environmental protection.

IoT System architecture

Sensor: Collects various physical quantity data, such as temperature, humidity, pressure, etc.

ARMxy Based Single Board Computer : Collects sensor data and writes it to InfluxDB.

InfluxDB: Stores and manages time series data, and provides query and analysis interfaces.

Front-end application: Based on InfluxDB data, develops various visualization applications to display and analyze data. Grafana, IgnitionSCADA etc.,

Technical implementation details

Data collection: Use C/C++, Python and other languages to write data collection programs and communicate with sensors through RS485/RS232, CAN/GPIO/DIN/DO/AIN/AO/RTD/TC etc.,

Data writing: Use the InfluxDB client library to write the collected data to InfluxDB.

Data query: Use InfluxDB's query language (Flux) to query and analyze the stored data.

Data visualization: Use visualization tools such as Grafana and Kibana to visualize the query results.

Read more:

InfluxDB on AWS

AWS InfluxDB

As of right now, Amazon Timestream supports InfluxDB as a database engine. With the help of this functionality, you can easily execute time-series applications in close to real-time utilizing InfluxDB and open-source APIs, such as the open-source Telegraf agents that gather time-series observations.

InfluxDB vs AWS Timestream

Timestream now offers you a choice between two database engines: Timestream for InfluxDB and Timestream for LiveAnalytics.

If your use cases call for InfluxDB capabilities like employing Flux queries or near real-time time-series queries, you should utilize the Timestream for InfluxDB engine. If you need to conduct SQL queries on petabytes of time-series data in seconds and ingest more than tens of terabytes of data per minute, the Timestream for LiveAnalytics engine currently in use is a good alternative.

You may utilize a managed instance that is automatically configured for maximum availability and performance with Timestream’s support for InfluxDB. Setting up multi-Availability Zone support for your InfluxDB databases is another way to boost resilience.

Timestream for LiveAnalytics and Timestream for InfluxDB work in tandem to provide large-scale, low-latency time-series data intake.

How to create database in InfluxDB

You can start by setting up an instance of InfluxDB. Now you can open the Timestream console, choose Create Influx database under InfluxDB databases in Timestream for InfluxDB.

You can provide the database credentials for the InfluxDB instance on the next page.

You can also define the volume and kind of storage to meet your requirements, as well as your instance class, in the instance configuration.

You have the option to choose either a single InfluxDB instance or a multi-Availability Zone deployment in the following section, which replicates data synchronously to a backup database in a separate Availability Zone. Timestream for InfluxDB in a multi-AZ deployment will immediately switch to the backup instance in the event of a failure, preserving all data.

Next, you can set up your connectivity setup to specify how to connect to your InfluxDB instance. You are able to configure the database port, subnets, network type, and virtual private cloud (VPC) in this instance. Additionally, you may choose to make your InfluxDB instance publicly available by configuring public subnets and setting the public access to publicly accessible. This would enable Amazon Timestream to provide your InfluxDB server with a public IP address. Make sure you have appropriate security measures in place to safeguard your InfluxDB instances if you decide to go with this option.

You had been configured your InfluxDB instance to be not publicly available, which restricts access to the VPC and subnets you specified earlier in this section.

You may provide the database parameter group and the log delivery settings once you’ve set up your database connection. You may specify the adjustable parameters your wish to utilize for your InfluxDB database in the parameter group. You may also specify which Amazon Simple Storage Service (Amazon S3) bucket you have to export the system logs from in the log delivery settings. Go to this page to find out more about the Amazon S3 bucket’s mandatory AWS Identity and Access Management (IAM) policy.

After that are you satisfied with the setup, you can choose Create Influx database.

You can see further details on the detail page once your InfluxDB instance is built.

You can now access the InfluxDB user interface (UI) once the InfluxDB instance has been established. By choosing InfluxDB UI in the console, you may see the user interface if you have your InfluxDB set up to be publicly available. As instructed, you made your InfluxDB instance private. SSH tunneling is needed to access the InfluxDB UI from inside the same VPC as my instance using an Amazon EC2 instance.

The URL endpoint from the detail page lets me connect in to the InfluxDB UI using your username and password from creation.Image credit to AWS

Token creation is also possible using the Influx command line interface (CLI). You can establish a setup to communicate with your InfluxDB instance before you generate the token.

You may now establish an operator, all-access, or read/write token since you have successfully built the InfluxDB setup. An example of generating an all-access token to authorize access to every resource inside the specified organization is as follows:

You may begin feeding data into your InfluxDB instance using a variety of tools, including the Telegraf agent, InfluxDB client libraries, and the Influx CLI, after you have the necessary token for your use case.

At last, you can use the InfluxDB UI to query the data. You can open the InfluxDB UI, go to the Data Explorer page, write a basic Flux script, and click Submit.

You may continue to use your current tools to communicate with the database and create apps utilizing InfluxDB with ease thanks to Timestream for InfluxDB. You may boost your InfluxDB data availability with the multi-AZ setup without having to worry about the supporting infrastructure.

AWS and InfluxDB collaboration

In celebration of this launch, InfluxData’s founder and chief technology officer, Paul Dix, shared the following remarks on this collaboration:

The public cloud will fuel open source in the future, reaching the largest community via simple entry points and useful user interfaces. On that aim, Amazon Timestream for InfluxDB delivers. Their collaboration with AWS makes it simpler than ever for developers to create and grow their time-series workloads on AWS by using the open source InfluxDB database to provide real-time insights on time-series data.

Important information

Here are some more details that you should be aware of:

Availability:

Timestream for InfluxDB is now widely accessible in the following AWS Regions: Europe (Frankfurt, Ireland, Stockholm), Asia Pacific (Mumbai, Singapore, Sydney, Tokyo), US East (Ohio, N. Virginia), and US West (Oregon).

Migration scenario:

Backup InfluxDB database

You may easily restore a backup of an existing InfluxDB database into Timestream for InfluxDB in order to move from a self-managed InfluxDB instance. You may use Amazon S3 to transfer Timestream for InfluxDB from the current Timestream LiveAnalytics engine. Visit the page Migrating data from self-managed InfluxDB to Timestream for InfluxDB to learn more about how to migrate data for different use cases.

Version supported by Timestream for InfluxDB: At the moment, the open source 2.7.5 version of InfluxDB is supported.

InfluxDB AWS Pricing

Visit Amazon Timestream pricing to find out more about prices.