InfiniteGraph vs LadybugDB
InfiniteGraph
objectivity.comLadybugDB
ladybugdb.comSide by side
| Figure | InfiniteGraph | LadybugDB |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | Yes | — |
| Open source | — | — |
| Web | — | Yes |
| Windows | Yes | Yes |
| macOS | — | Yes |
| Linux | Yes | Yes |
| iOS | — | Yes |
| Android | — | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Graph Databases | 7.7 (#21) | 8.2 (#11) |
| Deployment | InfiniteGraph is available for on-premise use and can be deployed in any cloud environment. | Ladybug runs embedded in an application process and does not require managing a separate database server. |
| Product | InfiniteGraph is a graph database and graph analytics platform. | Ladybug is an embedded graph database optimized for complex analytical workloads on very large graphs. |
| Support | A 2010 release says developer licenses starting at $999 per year included support. | The site lists community support and says commercial enterprise support contracts are available. |
Plans
In their own words
InfiniteGraph
InfiniteGraph has no write-up on Specifiction yet; its figures are above.
LadybugDB
LadybugDB is an embedded columnar graph database for analytical workloads and agentic applications. It uses Cypher with a structured property graph model and can run on disk or in memory; in-memory data is lost when the process ends. Its query engine uses columnar disk storage, vectorized and factorized processing, multi-core parallelism, and join algorithms. Transactions are atomic, durable, and serializable. The project distributes source code and precompiled binaries under the MIT License, which permits commercial and proprietary applications. Imports support Parquet, CSV, JSON, NumPy, Pandas or Polars DataFrames, and PyArrow Tables. Official client APIs are listed for Python, Node.js, Java, Rust, Go, Swift, C, and C++, alongside a command-line interface. Ladybug Explorer provides a browser-based way to query and visualize a database, and the MCP Server exposes a database to LLMs and agents. Extensions cover sources and systems including Azure storage, Delta Lake, DuckDB, Iceberg, PostgreSQL, and vector similarity search. Concurrent access permits one read-write Database object or multiple read-only objects; multiple processes needing writes should use an API server pattern.