![\"Dragonfly\"](\"/.github/images/logo-full.svg\"\n){kind=logo}
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![](\"http://static.dragonflydb.io/repo-assets/aws-throughput.svg\")
\n\nIf we compare Dragonfly and Redis on","github_created_at":"2021-12-11T10:00:42+00:00","created_at":"2026-07-11T11:32:47.952022+00:00","updated_at":"2026-08-23T00:00:57.036713+00:00","categories":[{"slug":"vector-databases","name":"Vector Databases","url":"https://www.graphcanon.com/categories/vector-databases","markdown_url":"https://www.graphcanon.com/categories/vector-databases.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/vector-databases"}],"tags":[{"slug":"cache","name":"cache"},{"slug":"cpp","name":"cpp"},{"slug":"database","name":"database"},{"slug":"fibers","name":"fibers"},{"slug":"in-memory","name":"in-memory"},{"slug":"key-value","name":"key-value"},{"slug":"memcached","name":"memcached"},{"slug":"message-broker","name":"message-broker"}],"trust":{"provenance":{"is_fork":false,"github_id":437245741,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-23T00:00:56.211Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":3,"days_since_push":0,"last_release_at":"2026-08-06T06:54:05Z","stars_delta_30d":115,"open_issues_delta_30d":9},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:32:49.117Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-23T00:00:56.733Z"},"languages":{"value":["c++","python"],"source":"github.language+pyproject.toml","observed_at":"2026-08-23T00:00:56.733Z"},"license_spdx":{"value":"Other","source":"github.license","observed_at":"2026-08-23T00:00:56.733Z"}},"decision_facts":{"hosting":null,"pricing":{"model":"unknown","summary":"The specific cost structure for using DragonflyDB is not documented in this repository content."},"requirements":{"notes":["DragonflyDB is most effective in environments capable of leveraging multi-threading and low-level optimization features"],"min_ram_gb":4,"requires_docker":false},"constraints":{"min_ram_gb":4,"pricing_model":"unknown","requires_docker":false},"when_to_use":["If your application requires high-performance vector search within a unified platform, DragonflyDB integrates this capability out-of-the-box.","Preferring native C++ implementation can lead to significant performance benefits in scenarios where low-level operations and integration are crucial."],"when_not_to_use":["When a smaller footprint is required due to limited resources or preference for lightweight solutions, older but more established tools like Memcached may be preferable.","If your ecosystem already heavily relies on Redis-specific features that have been built over years of use and customization, DragonflyDB might not offer the same level of compatibility or feature set"],"source":"enrich:decision_facts","observed_at":"2026-07-11T13:01:46.172Z"},"constraint_facets":{"min_ram_gb":4,"pricing_model":"unknown","requires_docker":false},"decision_summary":[{"label":"Pricing","value":"unknown - The specific cost structure for using DragonflyDB is not documented in this repository content."},{"label":"Requirements","value":"Min 4 GB RAM; DragonflyDB is most effective in environments capable of leveraging multi-threading and low-level optimization features"},{"label":"Adopt for","value":"DragonflyDB positions itself as an advanced cache and database solution that competes directly with established tools like Redis and Memcached while introducing key features such as efficient support for vector search."}]}}