The text discusses compression algorithms and their application in time-series data storage. Delta-delta encoding, Simple-8b, XOR-based compression, and dictionary compression are the key techniques used to reduce storage costs and speed up queries. These algorithms work by reducing the amount of information required to represent data objects, such as integers, timestamps, and floating-point numbers. By applying these algorithms, time-series datasets can be compressed to achieve 90%+ storage efficiencies, leading to significant cost savings and improved query performance. The text also highlights the importance of understanding compression techniques and their application in real-world scenarios, particularly in the context of time-series data.