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mkurman/zorai/lancedb

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PublishedJuly 29, 2026 at 12:07 PM

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version: "1.0.0" name: lancedb description: "LanceDB — serverless vector database for AI. Columnar storage on Lance format, zero-copy access, multimodal search (text + images + audio), and direct DataFrame integration. No separate server." tags: [lancedb, vector-database, embedded, multimodal, embeddings, python, zorai]

Overview

LanceDB is a developer-friendly, serverless vector database built on the Lance columnar format. It supports multimodal search (text, image, audio embeddings), hybrid search, and efficient streaming ingestion without a separate server process.

Installation

bash

uv pip install lancedb

Create and Query

python

import lancedb
import numpy as np
db = lancedb.connect("./my_lancedb")
table = db.create_table("vectors", [
    {"vector": np.random.rand(128), "text": "hello world"},
    {"vector": np.random.rand(128), "text": "goodbye moon"},
])
results = table.search(np.random.rand(128)).limit(5).to_list()
print([r["text"] for r in results])

Open-Clip Embeddings

python

import lancedb
from lancedb.embeddings import with_open_clip
@with_open_clip
class Images:
    image: str
    vector: list
table = db.create_table("images", schema=Images)
table.add([{"image": "photo.jpg"}, {"image": "diagram.png"}])
results = table.search("sunset landscape").limit(3).to_pandas()

References

All versions