Create a table, insert a document, and search it. Every other endpoint builds on these three.

curl -X POST http://localhost:8080/db/v1/tables/knowledge \
  -H "Content-Type: application/json" \
  -d '{}'

curl -X POST http://localhost:8080/db/v1/tables/knowledge/batch \
  -H "Content-Type: application/json" \
  -d '{"inserts":{"doc-1":{"content":"Antfly keeps the retrieval pipeline inside the engine."}},"sync_level":"full_text"}'

curl -X POST http://localhost:8080/db/v1/query \
  -H "Content-Type: application/json" \
  -d '{"table":"knowledge","full_text_search":{"query":"content:pipeline"},"fields":["content"],"limit":5}'

Reference

Antfly Public API

Antfly is a distributed key-value store and vector search engine built on a multi-Raft consensus architecture. It combines the best of traditional databases with modern AI capabilities to deliver hybrid search at scale.

Cluster Management

Monitor and manage your Antfly cluster's health and status.

Table Management

Manage tables in your Antfly cluster. Tables store your documents and support multiple indexes.

Data Operations

Perform data operations including batch inserts/deletes, linear merge sync, backup/restore, and individual key lookups.

Query Operations

Execute queries across tables using full-text search, vector similarity search, or hybrid approaches combining both with Reciprocal Rank Fusion (RRF).

Index Management

Create and manage indexes for full-text search, vector similarity search, and multimodal content.