{"categories":[{"label":"Database","url":"https://skillfed.io/packages/category/database/4"}],"enrichment":{"capability":"Embeddable graph database with Cypher query support, full-text search, vector indices, and columnar storage optimized for analytical workloads on large datasets.","skillfed_tags":["graph-database","embedded-db","cypher-query"],"use_cases":["Build knowledge graphs or recommendation engines with full-text and vector search on large node/edge datasets.","Run analytical queries on property graphs in embedded applications without deploying a separate database server.","Prototype or deploy graph-based machine learning pipelines that require join operations and columnar storage.","Query complex relational data using Cypher in a serverless, single-process context for edge computing or desktop tools.","Combine semantic search with structured graph queries in applications requiring both capabilities."],"what_it_does":"Real-ladybug is a Python binding for Ladybug, an embedded graph database designed to run directly within applications without a separate server. It implements a property graph model with Cypher query language support, allowing you to store and query complex relational data as nodes and edges. The database is optimized for analytical workloads on large datasets, combining columnar disk-based storage with specialized index structures (full-text search, vector indices, and sparse row-based adjacency lists) to accelerate query execution.\n\nThe package provides serverless, embeddable integration\u2014you can create in-memory or file-backed databases and execute queries directly from Python without managing a separate database process. It includes multi-core query parallelism, ACID transactions, and WebAssembly bindings for browser execution. With no runtime dependencies beyond the precompiled binary, deployment is straightforward once the platform-specific wheel is installed.","worth_installing":"Yes, if you need an embeddable graph database with Cypher support and analytical query optimization. The permissive MIT license, active maintenance, zero runtime dependencies, and broad platform coverage make it low-risk to try. Medium install friction is acceptable for a compiled database engine. No known vulnerabilities. Best suited for applications that want graph querying without managing a separate database server."},"id":"real-ladybug","links":{"html":"https://skillfed.io/packages/real-ladybug","md":"https://skillfed.io/packages/real-ladybug.md","pypi":"https://pypi.org/project/real-ladybug/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-04-01","license_spdx":null,"license_treatment":"permissive","name":"real-ladybug","python_support":"unspecified","summary":"Highly scalable, extremely fast, easy-to-use embeddable graph database"},"popularity":{"monthly_downloads":102570,"position":12860,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.15.3"}