Search

{
  "count": 3,
  "fetched_at": "2026-10-07T17:01:23.760Z",
  "latencyMs": 1031,
  "n": 3,
  "pages_loaded": 1,
  "query": "best open source vector database",
  "results": [
    {
      "domain": "zenml.io",
      "published": "2025-10-01T00:00:00.000Z",
      "rank": 1,
      "snippet": "Milvus is a highly scalable, open-source vector database. Built with a cloud-native, distributed architecture that separates compute and storage, Milvus can sca",
      "text": "On this pageThe choice of Vector database for RAG pipelines can make or break your agent’s core paradigm.\nA well-chosen vector store recalls relevant documents with low query latency, and a poor choice can slow down responses and cause…",
      "title": "We Tried and Tested 10 Best Vector Databases for RAG Pipelines - ZenML Blog",
      "url": "https://www.zenml.io/blog/vector-databases-for-rag"
    },
    {
      "domain": "reddit.com",
      "published": null,
      "rank": 2,
      "snippet": "Wow, all the answers here are good answers (yep, those are vector databases), but there's no context or reasoning besides u/electric_hotdog2k 's suggestion of M",
      "text": null,
      "title": "r/MachineLearning on Reddit: What's the best Vector DB? What's new in vector db and how is one better than other? [D]",
      "url": "https://www.reddit.com/r/MachineLearning/comments/1ijxrqj/whats_the_best_vector_db_whats_new_in_vector_db/"
    },
    {
      "domain": "milvus.io",
      "published": null,
      "rank": 3,
      "snippet": "Based on our research, Milvus was selected as the vector database of choice (over Chroma and Pinecone). Milvus is an open-source vector database designed specif",
      "text": null,
      "title": "Milvus | High-Performance Vector Database Built for Scale",
      "url": "https://milvus.io/"
    }
  ],
  "source": "brave"
}

# bash or zsh: see the payment challenge. Nothing is charged.
curl -sS -g -i 'https://x402-seller-pmlm.onrender.com/search?n=3&q=best+open+source+vector+database'

# x402 v2 sends the challenge base64-encoded in the PAYMENT-REQUIRED header (v1 sends it in the body).
# To read the header:
curl -sS -g -o /dev/null -D - 'https://x402-seller-pmlm.onrender.com/search?n=3&q=best+open+source+vector+database' \
  | grep -i '^payment-required:' | cut -d' ' -f2 | tr -d '\r' | base64 --decode

// npm i @x402/fetch @x402/evm viem
import { wrapFetchWithPayment, x402Client } from "@x402/fetch";
import { registerExactEvmScheme } from "@x402/evm/exact/client";
import { privateKeyToAccount } from "viem/accounts";

// Pays at most $0.01 per call.
const client = new x402Client().setSpendControls({ maxAmountPerPayment: "$0.01" });
registerExactEvmScheme(client, { signer: privateKeyToAccount(process.env.EVM_PRIVATE_KEY) });
const pay = wrapFetchWithPayment(fetch, client);

// Not sure it's safe to pay? ToolVet checks it first for $0.005. Pay for that from a separate
// client: this one is capped at $0.01 per payment. GET https://toolvet.app/api/v1/check?url=https%3A%2F%2Fx402-seller-pmlm.onrender.com%2Fsearch
const res = await pay("https://x402-seller-pmlm.onrender.com/search?n=3&q=best+open+source+vector+database");
console.log(res.status, await res.text());

# pip install "x402[requests,evm]"
import os
from eth_account import Account
from x402 import x402ClientSync
from x402.http.clients import x402_requests
from x402.mechanisms.evm import EthAccountSigner
from x402.mechanisms.evm.exact.register import register_exact_evm_client

# Pays at most $0.01 per call.
client = x402ClientSync().set_spend_controls({"max_amount_per_payment": "$0.01"})
register_exact_evm_client(client, EthAccountSigner(Account.from_key(os.environ["EVM_PRIVATE_KEY"])))

with x402_requests(client) as session:
    res = session.get("https://x402-seller-pmlm.onrender.com/search?n=3&q=best+open+source+vector+database")
    print(res.status_code, res.text)