Google Custom Search JSON API Alternative (2026): Cut $5/1K to $0.20/1K & Remove the 10K/Day Cap

import requests

# Replaces https://www.googleapis.com/customsearch/v1?key=...&cx=...&q=...
res = requests.get(
    "https://api.searchdataapi.com/v1/search",
    params={"q": "best vector database for rag 2026", "country": "us", "lang": "en", "limit": 10},
    headers={"Authorization": "Bearer sr_live_your_api_key"},
    timeout=15,
).json()

items = res["data"]["organic_results"]

// Replaces googleapis.com/customsearch/v1
const res = await fetch(
  "https://api.searchdataapi.com/v1/search?q=best+vector+database+for+rag+2026&country=us&lang=en&limit=10",
  { headers: { Authorization: "Bearer sr_live_your_api_key" } }
);
const { data } = await res.json();
console.log(data.organic_results);

curl -s "https://api.searchdataapi.com/v1/search?q=best+vector+database+for+rag+2026&country=us&lang=en&limit=10" \
  -H "Authorization: Bearer sr_live_your_api_key"

{
  "code": 0,
  "message": "success",
  "data": {
    "query": "best vector database for rag 2026",
    "country": "us",
    "lang": "en",
    "total_results": 10,
    "organic_results": [
      {
        "rank": 1,
        "title": "Best Vector Databases for Production RAG in 2026 — Benchmark",
        "url": "https://supabase.com/blog/vector-database-rag-benchmark",
        "domain": "supabase.com",
        "snippet": "Compare pgvector, Qdrant, Pinecone, and Weaviate across recall@10, p95 query latency, and hybrid BM25 + dense vector indexing."
      },
      {
        "rank": 2,
        "title": "Qdrant vs Pinecone vs pgvector: Choosing a RAG Vector Store",
        "url": "https://qdrant.tech/benchmarks/",
        "domain": "qdrant.tech",
        "snippet": "Filtered HNSW vector search benchmarks at 10M and 100M embeddings with quantization memory footprints."
      }
    ],
    "people_also_ask": [
      {
        "question": "Which vector database is fastest for RAG?",
        "answer": "In-memory Rust engines like Qdrant and Milvus achieve sub-10ms p95 latency at 10M+ vectors, while PostgreSQL pgvector (HNSW) simplifies transactional hybrid search."
      }
    ],
    "related_searches": [
      "pgvector vs qdrant",
      "hybrid search rag pipeline",
      "langchain vector store"
    ]
  },
  "meta": {
    "credits_charged": 2,
    "credits_remaining": 11998
  }
}