Python Cache Libraries
Cache libraries for Python
GitHub Star Comparison
| No | Name | GitHub Stars | Description | Trend | License | Type | Official Site |
|---|---|---|---|---|---|---|---|
| 1 | Django Cache | ⭐ 85.5k | Comprehensive caching system built into Django framework. Supports multiple cache backends | Widely used as standard cache solution for Django projects in 2025 | BSD | Web Framework Cache | Official |
| 2 | Redis-py | ⭐ 13.3k | Most popular official Redis client for Python. Provides high-performance distributed caching solution with rich features and RESP3 support | Continues growing in 2025 as the standard library for Redis distributed caching. Expanding adoption in large-scale applications | MIT | Redis Client | Official |
| 3 | DiskCache | ⭐ 2.6k | Pure-Python disk-based cache library faster than Redis and Memcached. Supports persistence and GB-sized data storage | Rising attention in 2025. Increasingly chosen for applications requiring persistent caching of large datasets | Apache-2.0 | Persistent Cache | Official |
| 4 | Cachetools | ⭐ 2.6k | Lightweight in-memory caching library. Supports various eviction strategies like LRU, LFU, TTL with function decorators | Popular in small to medium applications in 2025. Continues to be chosen for its simplicity and rich eviction strategies | MIT | Memory Cache | Official |
| 5 | Beaker | ⭐ 537 | Legacy Python caching library. Supports various backends but migration to dogpile.cache is now recommended | Legacy status in 2025. dogpile.cache recommended for new development, usage declining | BSD | Legacy Cache | Official |
| 6 | Python-memcached | ⭐ 467 | Python client for Memcached. Provides access to simple and fast distributed caching system | Stable demand as traditional caching solution in 2025. Continued use in legacy systems | PSF | Memcached Client | Official |
| 7 | Dogpile.cache | ⭐ 281 | Advanced function result caching library. Successor to Beaker with excellent concurrency control and stampede protection | Maintains stable popularity in 2025. Steady adoption in enterprise applications | MIT | Memoization Cache | Official |