LadybugDB vs Quine
LadybugDB
ladybugdb.com
Quine
quine.ioSide by side
| Figure | LadybugDB | Quine |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | Yes |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | Yes |
| iOS | Yes | — |
| Android | Yes | — |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 2 |
| Spec score · Graph Databases | 8.2 (#11) | 7.6 (#23) |
| Deployment | Ladybug runs embedded in an application process and does not require managing a separate database server. | The maker provides Docker, a Java executable, and source-code distributions; the executable requires Java JRE 11 or newer. |
| Query language | It uses a property graph data model and Cypher query language. | Quine supports Cypher for graph queries and also documents Gremlin support. |
| Support | The site lists community support and says commercial enterprise support contracts are available. | Open-source users can get community support on Discord, while Enterprise includes professional support from thatDot. |
Plans
In their own words
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.