Redis various data types underlying data storage structure

Redis data types use different underlying storage structures: String: Simple Dynamic String (SDS) Hash: Hash table, use linked list or jump table to process hash collision list: Doubly linked list Collection: Ha Hash table or integer collection, using Bloom filter Sorted collection: skip table or dictionary Geospatial index: skip table or R tree

Redis Data type underlying storage structure

Redis is a high-performance NoSQL database that supports multiple data types, each type uses a different underlying storage structure.

String (string)

• Underlying storage structure: simple dynamic string (SDS)
• SDS uses pre-allocated memory to reduce Memory allocation and deallocation overhead.
• SDS can store binary or text data and supports efficient splicing and modification operations.

Hash(hash)

• Underlying storage structure: Hash table
• The hash table uses the hash function to Keys map to values.
• Each key is stored in the hash table and is represented by a pointer to the value.
• For each hash bucket, use a linked list or skip table to store hash collisions.

List (list)

• Underlying storage structure: doubly linked list
• Doubly linked list links elements into a sequential list.
• Each element in the linked list stores a pointer to the next element and the previous element.
• Linked lists support efficient insertion, deletion and search operations.

Set

• Underlying storage structure: hash table or integer set
• Use hash table to store elements , and use bloom filters for quick membership checks.
• The integer collection is only suitable for storing integers and adopts a more compact storage structure.

Ordered set (zset)

• Underlying storage structure: jump list or dictionary
• The jump table organizes elements into Multi-layer linked list to achieve efficient ordered search.
• Dictionaries store elements in hash tables and use skip tables to maintain order.

Geographic spatial index (geospatial)

• Underlying storage structure: skip table or R tree
• Jump table is used for storage The coordinates of a geospatial point.
• R tree is a hierarchical structure used for efficient search and range queries.

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