The Industrial Revolution marked a significant shift from manual work to mechanized manufacturing, transforming the way humans work. Today, we are in the midst of another industrial transformation, referred to as Industry 4.0, which involves feeding data into autonomous systems that enhance manufacturing processes. To generate consistent and predictable output, manufacturers have adopted physical instrumentation, such as sensors, to measure different aspects of a process. Critical context for this data is provided by time-series data, which includes a timestamp, allowing industrial operators to make sense of it. Industry 4.0 aims for interconnection, information transparency, technical assistance, and decentralized decisions. Time-series data plays a crucial role in almost every aspect of industrial operations, both physical and virtual. However, legacy data historians are not ideal for an Industry 4.0 system due to cost, vendor lock-in, scalability issues, poor developer experience, and siloed data. Instead, open-source time-series platforms like InfluxDB offer a more suitable replacement, providing flexibility and connectivity necessary to evolve industrial operations. By leveraging InfluxDB, manufacturers can harness data, provide critical information to workers on the factory floor, and add measurable value throughout the manufacturing process.