Approximate databases is a research area and system design paradigm focused on managing and querying data where exact results are not strictly required. It investigates techniques to process queries on massive datasets by trading off result precision for significant improvements in performance, scalability, and resource efficiency, often employing methods such as data summarization, sampling, and approximate query processing algorithms that provide results with quantifiable error bounds.