The author created a ‘cheat sheet’ to visually explain important data structures used in computer science and real-world applications, which is helpful for interview preparation. Understanding Big-O complexity is crucial for analyzing algorithm performance with increasing data size. They emphasize the RUM tradeoff (Read Efficiency, Update Efficiency, Memory Efficiency) when choosing data structures. The article covers key structures like arrays, linked lists, and trees, explaining their characteristics and performance. It also delves into specialized structures like skip lists, B+ trees, splay trees, and spatial trees. Unique mentions include Bloom filters, HAMTs, and Merkle trees, highlighting their efficiency and applications. Reference to external sources is provided for further reading.
https://photonlines.substack.com/p/visual-data-structures-cheat-sheet