Athenadb: store and query text embeddings

Understand the project

Practical overview

When it fits

Use Athenadb when an application needs a deployable API for text embedding and vector similarity search, and its Cloudflare Workers, D1 and Vectorize stack fits the project.

Who it is for

Developers building retrieval-augmented knowledge applications.
Teams that need an API for embedding, storing and searching text snippets in a Cloudflare-based stack.

Documented uses

Convert text into embeddings and store entries under a namespace.
Search stored entries for text with similar embeddings.
Generate embeddings without storing them.
List namespace entries, retrieve records by UUID, and delete records or a namespace.

Before you choose

Requirements & limits

The README says Athenadb requires a $5/month Cloudflare Workers subscription. It documents deployment using Wrangler and provides an API URL after deployment.

Built with Cloudflare Workers, Workers AI, D1 and Vectorize; setup provisions a database and vector resource.
Insert and query requests accept individual text or batches, with each string limited to 1,024 characters.
Similarity queries return five results by default and allow up to 20; namespace listing allows up to 100 entries per request.
Deleting an entry or all entries in a namespace is documented as irreversible.
The repository specifies the AGPL-3.0 license.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Set up and deploy Athenadb on Cloudflare

Create the database and vector resources, initialize them, and deploy the Worker to obtain an API URL.

Before you start

Wrangler installed and authenticated with wrangler login.
A $5/month Cloudflare Workers subscription, required by the README.
The Athenadb repository and Cloudflare D1 and Vectorize resources.

Steps

Clone the repository and change into its directory.
Run the command below and the command below.
Documented command
```
npm run create-vector
```
Documented command
```
npm run create-db
```
Copy the generated Database ID into wrangler.toml under database_id.
Run the command below and then the command below; the deployment output provides the API URL.
Documented command
```
npm run init-db
```
Documented command
```
npm run deploy
```

Expected outcome

A deployed Worker and API URL for the documented Athenadb endpoints.

Guide limitations

This guide covers setup and deployment, not a verified execution test.
The documented subscription requirement is $5 per month.
The documented setup depends on Cloudflare Workers, D1 and Vectorize.

Documentation 1 ↗

COMPARE OPTIONS

Compare options for Vector search

These projects document a common task and share a project role. This is a source-based comparison, not an execution benchmark or a guarantee of interchangeability.

Project	Documented purpose	Platform	Access and requirements
Athenadb	Convert text into embeddings and store entries under a namespace.	Cloud, Server	The README says Athenadb requires a $5/month Cloudflare Workers subscription. It documents deployment using Wrangler and provides an API URL after deployment.
Chatbot with PDF for Semantic Search	Prepare document content as embeddings and save it to a supported vector database.	Web	The repository is identified as open source and publicly visible on GitHub.
AI LLM Playground	Ask questions about PDF documents through an assistant interface.	Web

Evidence and transparency

Sources & review

Official repository ↗

Source record details

Source availability: Active
Sources checked: 17 October 2026
Original website title: TimeSurgeLabs/athenadb · Official homepage title · retained in its source language

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Athenadb