Hash tables changed search by using extra memory and a computed address to make dictionary operations expected constant time, turning collision handling and load factor into central design choices.
Union-find evolved from early equivalence-class algorithms into one of the most efficient general-purpose data structures, with tree weighting and path compression giving sequences of set operations an inverse-Ackermann time bound.
Robert Tarjan transformed depth-first search from a traversal routine into a design method for linear-time graph algorithms, data structures, planarity, connectivity, and set operations.
Rudolf Bayer and Edward McCreight designed the B-tree to keep large ordered indexes balanced on page-oriented storage, making logarithmic search and dynamic updates practical on disks.
Redis made in-memory data structures themselves the database interface, pairing simple key-based commands with lists, sets, sorted sets, persistence and replication for real-time applications.