KNX and DuckDB Integration
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Powerful Performance, Limitless Scale
Collect, organize, and act on massive volumes of high-velocity data. Any data is more valuable when you think of it as time series data. with InfluxDB, the #1 time series platform built to scale with Telegraf.
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Input and output integration overview
The KNX plugin listens for messages from the KNX home-automation bus via a KNX-IP interface, allowing for real-time data integration from KNX-enabled devices.
This plugin enables Telegraf to write structured metrics into DuckDB using SQLite-compatible SQL connections, supporting lightweight local analytics and offline metric analysis.
Integration details
KNX
The KNX plugin allows for the listening to messages transmitted over the KNX home-automation bus. It establishes a connection with the KNX bus through a KNX-IP interface, making it compatible with various message datapoint types that KNX employs. The plugin supports service input configuration, wherein it remains active to listen for relevant metrics or events rather than relying solely on scheduled intervals. This inherent characteristic enables real-time data capture from the KNX systems, enhancing automation and integration possibilities for building management and smart home applications. Additionally, this plugin is designed to handle multiple measurements from the KNX data, allowing for a flexible categorization of metrics based on the derived datapoint types, thus broadening the scope of data integration in smart environments.
DuckDB
Use the Telegraf SQL plugin to write metrics into a local DuckDB database. DuckDB is an in-process OLAP database designed for efficient analytical queries on columnar data. Although it does not provide a traditional client-server interface, DuckDB can be accessed via SQLite-compatible drivers in embedded mode. This allows Telegraf to store time series metrics in DuckDB using SQL, enabling powerful analytics workflows using familiar SQL syntax, Jupyter notebooks, or integration with data science tools like Python and R. DuckDB’s columnar storage and vectorized execution make it ideal for compact and high-performance metric archives.
Configuration
KNX
[[inputs.knx_listener]]
## Type of KNX-IP interface.
## Can be either "tunnel_udp", "tunnel_tcp", "tunnel" (alias for tunnel_udp) or "router".
# service_type = "tunnel"
## Address of the KNX-IP interface.
service_address = "localhost:3671"
## Measurement definition(s)
# [[inputs.knx_listener.measurement]]
# ## Name of the measurement
# name = "temperature"
# ## Datapoint-Type (DPT) of the KNX messages
# dpt = "9.001"
# ## Use the string representation instead of the numerical value for the
# ## datapoint-type and the addresses below
# # as_string = false
# ## List of Group-Addresses (GAs) assigned to the measurement
# addresses = ["5/5/1"]
# [[inputs.knx_listener.measurement]]
# name = "illumination"
# dpt = "9.004"
# addresses = ["5/5/3"]
DuckDB
[[outputs.sql]]
## Use the SQLite driver to connect to DuckDB via Go's database/sql
driver = "sqlite3"
## DSN should point to the DuckDB database file
dsn = "file:/var/lib/telegraf/metrics.duckdb"
## SQL INSERT statement with placeholders for metrics
table_template = "INSERT INTO metrics (timestamp, name, value, tags) VALUES (?, ?, ?, ?)"
## Optional: manage connection pooling
# max_open_connections = 1
# max_idle_connections = 1
# conn_max_lifetime = "0s"
## DuckDB does not require TLS or authentication by default
Input and output integration examples
KNX
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Smart Home Energy Monitoring: Utilize the KNX plugin to monitor energy consumption across various devices in a smart home setup. By configuring measurements for different appliances, users can gather real-time data on power usage, enabling them to optimize energy consumption and reduce costs. This setup can also integrate with visualization tools to provide insights into energy trends and usage patterns.
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Automated Lighting Control System: Leverage this plugin to listen for lighting status updates from KNX sensors in a building. By capturing measurements related to illumination, users can develop an automated lighting control system that adjusts the brightness based on the time of day or occupancy, enhancing comfort and energy efficiency.
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HVAC Performance Tracking: Implement the KNX plugin to track temperature and ventilation data across different zones in a building. By monitoring these metrics, facilities managers can identify trends in HVAC performance, optimize climate control strategies, and proactively address maintenance needs to ensure consistent environmental quality.
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Integrated Security Solutions: Use the plugin to capture data from KNX security sensors, such as door/window open/close statuses. This information can be routed into a central monitoring system, providing real-time alerts and enabling automated responses, such as locking doors or activating alarms, thus enhancing the building’s security posture.
DuckDB
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Embedded Metric Warehousing for Notebooks: Write metrics to a local DuckDB file from Telegraf and analyze them in Jupyter notebooks using Python or R. This workflow supports reproducible analytics, ideal for data science experiments or offline troubleshooting.
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Batch Time-Series Processing on the Edge: Use Telegraf with DuckDB on edge devices to log metrics locally in SQL format. The compact storage and fast analytical capabilities of DuckDB make it ideal for batch processing and low-bandwidth environments.
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Exploratory Querying of Historical Metrics: Accumulate system metrics over time in DuckDB and perform exploratory data analysis (EDA) using SQL joins, window functions, and aggregates. This enables insights that go beyond what typical time-series dashboards provide.
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Self-Contained Metric Snapshots: Use DuckDB as a portable metrics archive by shipping
.duckdb
files between systems. Telegraf can collect and store data in this format, and analysts can later load and query it using the DuckDB CLI or integrations with tools like Tableau and Apache Arrow.
Feedback
Thank you for being part of our community! If you have any general feedback or found any bugs on these pages, we welcome and encourage your input. Please submit your feedback in the InfluxDB community Slack.
Powerful Performance, Limitless Scale
Collect, organize, and act on massive volumes of high-velocity data. Any data is more valuable when you think of it as time series data. with InfluxDB, the #1 time series platform built to scale with Telegraf.
See Ways to Get Started
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