In the context of Industrial Internet of Things (IIoT), managing highly contextualized data is crucial for improving productivity, streamlining operations, and gaining in-depth insights. High-cardinality data, which includes identifiers, device IDs, sensor serial numbers, and tags, offers a complete understanding of specific hardware and operations, enabling jobs like predictive maintenance and in-depth analysis. However, this type of data also presents challenges such as massive volume and complexity, storage and scalability issues, data query performance limitations, increased complexity in data management, cost of infrastructure, difficulty in anomaly detection, and data privacy and security risks. InfluxDB, a leading time series database (TSDB), stores high-cardinality data without impacting performance and offers features like effective data ingestion, horizontal scaling, advanced compression techniques, dynamic query performance, data retention, and querying and analysis capabilities to manage and analyze complex high-cardinality data with ease, empowering organizations to make smarter and faster decisions, optimize processes, and stay ahead in a competitive industrial landscape.