InfluxDB Connector
High-Performance Data Pipeline for Time-Series Data
InfluxDB Connector enables seamless data ingestion from OPC and SQL-based sources into InfluxDB. Built for time-series workloads, it processes large volumes of industrial data with low latency and high reliability.
With built-in retention and downsampling mechanisms, it efficiently manages the data lifecycle, reducing storage costs while maintaining analytical performance. It is an ideal solution for real-time monitoring, reporting, and advanced analytics.
Get Demo
The problem
Difficult to manage time series data from different data sources (OPC / SQL)
Rapidly increasing storage costs due to high data volume
Performance and latency issues in real-time data streams
Solution
Seamless and reliable data transfer from OPC and SQL data sources to InfluxDB
Automated management of the data lifecycle with retention and downsampling
Low latency and high scalability with high-performance time series processing
Highlights
Time Series Data Flow Structure
Continuous and reliable data collection from OPC and SQL based systems.
High-performance data transfer and processing infrastructure optimised for time series data.
Real-time monitoring, reporting and advanced analytical scenarios.
Independent & Security Oriented
Frequently Asked Questions
Which data sources does InfluxDB Connector support?
It supports OPC and SQL-based industrial data sources and integrates with InfluxDB.
Are there performance problems with large data volumes?
No. It offers high performance thanks to its architecture optimised for time series data.
Are retention and downsampling managed automatically?
Yes, the data lifecycle is managed automatically. The data lifecycle is managed automatically and no manual intervention is required.
Is real-time data monitoring possible?
Yes, it is possible. Real-time monitoring and reporting can be done thanks to instant data flow.
Is it suitable for analytical scenarios?
Description. It is an ideal solution for advanced analytical and reporting scenarios.