1 year ago

Data collection is one of the biggest challenges when working with databases. These use cases often involve a large number of systems, sensors and data sources, and they don’t always output data in the same formats or use the same protocols. When it comes to time series data, this challenge becomes even greater because of the sheer number of data sources, and the rates at which they generate data mean you might need to ingest millions of data points every second.

We want to collect data from the generators, store it in https://www.influxdata.com/products/?utm_source=vendor&utm_medium=referral&utm_campaign=2022-10_spnsr-ctn_iot-edge-hybrid-data-collection_tns, process and analyze that data, and then send that processed data on for use elsewhere.

Partitioning increases data throughput, so we can ensure that all that IoT data actually makes it to the data store, with the help of Kafka’s enterprise-level connectors.