Vercel

Vercel Runtime Cache

Cache data within Vercel Functions using the Runtime Cache API.

Usage

Driver name: vercel-runtime-cache

import { createStorage } from "unstorage";
import vercelRuntimeCacheDriver from "unstorage/drivers/vercel-runtime-cache";

const storage = createStorage({
  driver: vercelRuntimeCacheDriver({
    // base: "app",
    // ttl: 60, // seconds
    // tags: ["v1"],
  }),
});

Optional step: To allow using outside of vercel functions, install @vercel/functions in your project:

npm i @vercel/functions

yarn add @vercel/functions

pnpm i @vercel/functions

bun i @vercel/functions

deno i npm:@vercel/functions

Options

• base: Optional prefix to use for all keys (namespacing).
• ttl: Default TTL for all items in seconds.
• tags: Default tags to apply to all cache entries (Note: Will be merged with per-call option tags).

Per-call options

• ttl: Add TTL (in seconds) for this setItem call.
• tags: Apply tags to this setItem call.

Example:

await storage.setItem("user:123", JSON.stringify({ name: "Ana" }), {
  ttl: 3600,
  tags: ["user:123"],
});

To expire by tags:

await storage.clear("", { tags: ["user:123"] });

Limitations

• getKeys: The runtime cache API does not support listing keys; this returns [].
• clear: The runtime cache API does not support clearing by base; only tag-based expiration is supported.
• Metadata: Runtime cache does not expose metadata; getMeta is not implemented.
• Persistence: This is not a persistent store; it’s intended for request-time caching inside Vercel Functions.

Vercel KV

Store data in a Vercel KV Store.

Usage

Driver name: vercel-kv

import { createStorage } from "unstorage";
import vercelKVDriver from "unstorage/drivers/vercel-kv";

const storage = createStorage({
  driver: vercelKVDriver({
    // url: "https://<your-project-slug>.kv.vercel-storage.com", // KV_REST_API_URL
    // token: "<your secret token>", // KV_REST_API_TOKEN
    // base: "test",
    // env: "KV",
    // ttl: 60, // in seconds
  }),
});

To use, you will need to install @vercel/kv dependency in your project:

{
  "dependencies": {
    "@vercel/kv": "latest"
  }
}

Note: For driver options type support, you might need to install @upstash/redis dev dependency as well.

Options:

• url: Rest API URL to use for connecting to your Vercel KV store. Default is KV_REST_API_URL.
• token: Rest API Token to use for connecting to your Vercel KV store. Default is KV_REST_API_TOKEN.
• base: optional Prefix to use for all keys. Can be used for namespacing.
• env: optional Flag to customize environment variable prefix (Default is KV). Set to false to disable env inference for url and token options.
• scanCount: How many keys to scan at once.

See @upstash/redis for all available options.

Vercel Blob

Store data in a Vercel Blob Store.

Usage

Driver name: vercel-blob

To use, you will need to install @vercel/blob dependency in your project:

npm i @vercel/blob

yarn add @vercel/blob

pnpm i @vercel/blob

bun i @vercel/blob

deno i npm:@vercel/blob

import { createStorage } from "unstorage";
import vercelBlobDriver from "unstorage/drivers/vercel-blob";

const storage = createStorage({
  driver: vercelBlobDriver({
    access: "public", // Required! Beware that stored data is publicly accessible.
    // token: "<your secret token>", // or set BLOB_READ_WRITE_TOKEN
    // base: "unstorage",
    // envPrefix: "BLOB",
  }),
});

Options:

• access: Whether the blob should be publicly accessible. (required, must be public)
• base: Prefix to prepend to all keys. Can be used for namespacing.
• token: Rest API token to use for connecting to your Vercel Blob store. If not provided, it will be read from the environment variable BLOB_READ_WRITE_TOKEN.
• envPrefix: Prefix to use for token environment variable name. Default is BLOB (env name = BLOB_READ_WRITE_TOKEN).