DuckDB UI vs LadybugDB
DuckDB UI
duckdb.orgLadybugDB
ladybugdb.comSide by side
| Figure | DuckDB UI | LadybugDB |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| iOS | — | Yes |
| Android | — | Yes |
| API | — | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Embedded Databases | 8.3 (#8) | 8.4 (#7) |
Plans
In their own words
DuckDB UI
DuckDB UI is a free browser interface for a local DuckDB instance, added through the ui extension. Start it with `duckdb -ui` or `CALL start_ui()`; it opens in the default browser and is served by an HTTP server embedded in DuckDB, available by default at `http://localhost:4213`. The interface includes a SQL notebook with autocomplete and keyboard shortcuts, a catalog browser, a table explorer with column statistics, and a results viewer with sorting and filtering. The native DuckDB process gives it access to local cores, memory, and files. Queries run locally by default, and queries and data stay on the computer. Connecting to MotherDuck is optional and requires signing in. The UI is built and maintained by MotherDuck. The local server retrieves interface files from ui.duckdb.org, so alternate configured URLs should be trusted because the application can access loaded DuckDB data. The UI cannot be run directly against a read-only database and does not currently support windows_arm64.
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.