Quickstart - Upstash Documentation

1. Create Index

TypeScript
Python
Redis CLI

import { Redis, s } from "@upstash/redis";

const redis = Redis.fromEnv();

const index = await redis.search.createIndex({
  name: "products",
  dataType: "json",
  prefix: "product:",
  schema: s.object({
    name: s.string(),
    description: s.string(),
    category: s.string().noTokenize(),
    price: s.number(),
    inStock: s.boolean(),
  }),
});

from upstash_redis import Redis

redis = Redis.from_env()

index = redis.search.create_index(
    name="products",
    data_type="json",
    prefixes="product:",
    schema={
        "name": "TEXT",
        "description": "TEXT",
        "category": {"type": "TEXT", "notokenize": True},
        "price": "F64",
        "inStock": "BOOL",
    },
)

SEARCH.CREATE products ON JSON PREFIX 1 product: SCHEMA name TEXT description TEXT category TEXT NOTOKENIZE price F64 FAST inStock BOOL

Create an index once, not on every request. createIndex throws if an index with the same name already exists. To make setup safely re-runnable, pass exists_ok=True in the Python SDK, or wrap the call in a try/catch in TypeScript.

2. Add Data

Add data using standard Redis JSON commands. Any key matching the index prefix will be automatically indexed.

Writes are indexed asynchronously: a JSON.SET returns before the document is searchable. For demos and tests, call waitIndexing() / wait_indexing() to block until pending updates are applied. In production, queries running on a later request will normally hit an up-to-date index without waiting.

TypeScript
Python
Redis CLI

await redis.json.set("product:1", "$", {
  name: "Wireless Headphones",
  description:
    "Premium noise-cancelling wireless headphones with 30-hour battery life",
  category: "electronics",
  price: 199.99,
  inStock: true,
});

await redis.json.set("product:2", "$", {
  name: "Running Shoes",
  description: "Lightweight running shoes with advanced cushioning technology",
  category: "sports",
  price: 129.99,
  inStock: true,
});

await index.waitIndexing();

redis.json.set("product:1", "$", {
    "name": "Wireless Headphones",
    "description": "Premium noise-cancelling wireless headphones with 30-hour battery life",
    "category": "electronics",
    "price": 199.99,
    "inStock": True,
})

redis.json.set("product:2", "$", {
    "name": "Running Shoes",
    "description": "Lightweight running shoes with advanced cushioning technology",
    "category": "sports",
    "price": 129.99,
    "inStock": True,
})

index.wait_indexing()

JSON.SET product:1 $ '{"name": "Wireless Headphones", "description": "Premium noise-cancelling wireless headphones with 30-hour battery life", "category": "electronics", "price": 199.99, "inStock": true}'
JSON.SET product:2 $ '{"name": "Running Shoes", "description": "Lightweight running shoes with advanced cushioning technology", "category": "sports", "price": 129.99, "inStock": true}'

SEARCH.WAITINDEXING products

3. Search Data

TypeScript
Python
Redis CLI

const results = await index.query({
  filter: { description: "wireless" },
});

const count = await index.count({
  filter: { price: { $lt: 150 } },
});

results = index.query(filter={"description": "wireless"})

count = index.count(filter={"price": {"$lt": 150}})

SEARCH.QUERY products '{"description": "wireless"}'

SEARCH.COUNT products '{"price": {"$lt": 150}}'

Next Steps

Schema Definition

Define the fields you want to index and how they are matched

Querying

Learn the JSON-based query language with filters and operators

Aggregations

Group and summarize your indexed data with aggregation pipelines

Recipes

Complete, real-world examples you can adapt to your own use cases

​1. Create Index

​2. Add Data

​3. Search Data

​Next Steps

Schema Definition

Querying

Aggregations

Recipes

1. Create Index

2. Add Data

3. Search Data

Next Steps