AgensGraph vs LadybugDB
AgensGraph
skaiworldwide.comLadybugDB
ladybugdb.comSide by side
| Figure | AgensGraph | LadybugDB |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| 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 (#19) | 8.2 (#11) |
| Deployment | The maker documents Linux and Windows installation, while its current download page lists the Community Edition for Linux x86-64, Docker, and source code. | Ladybug runs embedded in an application process and does not require managing a separate database server. |
| Integrations | The maker lists PostgreSQL, standard SQL, JDBC, ODBC, Apache AGE, heterogeneous databases, and BI tools among the technologies it connects with. | The documentation describes integrations with Snowflake and PostgreSQL, and attaching to DuckDB, SQLite, Iceberg, Delta Lake, and Unity Catalog sources. |
| Product | AgensGraph is a hybrid relational and graph database that handles structured data and relationships in one engine. | Ladybug is an embedded graph database optimized for complex analytical workloads on very large graphs. |
| Support | The maker says its Korea-based engineers provide direct support and that PGTS maintenance provides deployment and operations SLAs. | The site lists community support and says commercial enterprise support contracts are available. |
Plans
In their own words
AgensGraph
AgensGraph 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.