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Target customers: 1. industry users in finance and insurance, e-commerce, gaming, advertising, and more. 2. users who require large-scale, low-cost, high-performance, and high-accuracy data deduplication. 3. users who find HyperLogLog (HLL) memory-intensive or insufficient in performance or accuracy. Features released: TairCpc. It is a high-performance data structure used for data deduplication. It counts different values as data streams and allows you to combine multiple data blocks and deduplicate the blocks to obtain a total number. Compressed Probability Counting (CPC) achieves the same level of accuracy as HLL with about 40% less memory. Developed based on open source CPC, TairCpc reduces error rate to 0.008%, as opposed to 0.67% of open source CPC and 1.95% of HLL. Main features: ● Low memory usage, incremental reads and writes, and minimal I/O. ● High-performance and ultra high-accuracy deduplication. ● Reduced stable error rate. Typical scenarios: ● Security systems for banks. ● Flash sales. ● Prevention and control of ticket scalping. ● Applicable scenarios of HLL and beyond.