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LynseDB is a vector database implemented purely in Python, designed to be lightweight, server-optional, and easy to deploy locally or remotely. It offers straightforward and clear Python APIs, aiming to lower the entry barrier for using vector databases.
It focuses on achieving 100% recall, prioritizing recall accuracy over high-speed search performance. This approach ensures that users can reliably retrieve all relevant vector data, making LynseDB particularly suitable for applications that require responses within hundreds of milliseconds.
LynseDB features¶
⚡ Server-optional, simple parameters, simple API.
⚡ Fast, memory-efficient, easily scales to millions of vectors.
⚡ Based on a generic Python software stack, platform-independent, highly versatile.
⚡ Recall-prioritized design, lifecycle search caching technology, FieldExpression fast filtering, Field multi-type indexing, and other user-centric features
Some Defects You Should Know¶
- Not yet backward compatible
LynseDB is actively being updated, and API backward compatibility is not guaranteed. You should use version numbers as a strong constraint during deployment to avoid unnecessary feature conflicts and errors.
- Data size constraints
Although our goal is to enable brute force search or inverted indexing on billion-scale vectors, we currently still recommend using it on a scale of millions of vectors or less for the best experience.
- Python's native api is not process-safe
The Python native API is recommended for use in single-process environments, whether single-threaded or multi-threaded; for ensuring process safety in multi-process environments, please use the HTTP API.
Installation¶
Prerequisite¶
- python version >= 3.9
- Owns one of the operating systems: Windows, macOS, or Ubuntu (or other Linux distributions). The recommendation is for the latest version of the system, but non-latest versions should also be installable, although they have not been tested.
- Memory >= 4GB, Free Disk >= 4GB.
Install Client API package (Mandatory)¶
If you wish to use Docker (Optional)¶
You must first install Docker on the host machine.
After installing the Client API package: