Pantry

Overview

Pantry is a Backend as a Service (BaaS) platform that specializes in providing a simple, persistent store for JSON data. Launched in 2014, it offers a RESTful API designed for developers who need to store and retrieve small to medium-sized JSON objects without the overhead of setting up and managing a traditional database. This approach makes Pantry particularly suitable for rapid prototyping, personal development projects, and as a backend for serverless applications or static sites that require dynamic content storage.

The core concept behind Pantry revolves around a "Pantry" – an isolated container for JSON data. Within each Pantry, developers can store multiple "baskets," which are individual JSON documents. The API supports standard HTTP methods (GET, POST, PUT, DELETE) for interacting with these baskets, allowing for CRUD (Create, Read, Update, Delete) operations on JSON data. Pantry emphasizes ease of use, often requiring no authentication for public Pantries, which simplifies initial development and testing. For scenarios requiring data privacy, private Pantries can be configured with API keys for restricted access.

Pantry's design philosophy prioritizes developer experience by abstracting away database complexities. Users do not need to define schemas, manage connections, or handle scaling – these aspects are managed by the service. This simplicity allows developers to focus on application logic rather than infrastructure. For instance, a front-end developer building a portfolio site might use Pantry to store dynamic project details or blog posts, retrieving them directly via JavaScript without needing a dedicated backend server. Similarly, an IoT project could use Pantry to log sensor data, or a mobile app prototype could store user preferences.

While Pantry excels in scenarios requiring quick data persistence and retrieval, it is important to note its focus on small to medium data sets and less complex querying. For applications demanding advanced database features like complex relational queries, transaction management, or petabyte-scale storage, alternative solutions might be more appropriate. However, for its target use cases – including rapid iteration, educational projects, and supplementing serverless functions – Pantry provides a functional and accessible data storage solution. The Pantry documentation details how to interact with the API and manage Pantries.

Key features

• JSON Data Storage: Store and retrieve arbitrary JSON objects within designated "baskets" inside "Pantries."
• RESTful API: Interact with data using standard HTTP methods (GET, POST, PUT, DELETE) for full CRUD operations.
• No-Auth Public Pantries: Option to create public Pantries that do not require API keys, simplifying development for non-sensitive data.
• API Key Authentication: Secure private Pantries with unique API keys to control access to stored data.
• Web Interface for Management: A user-friendly web dashboard to create, view, edit, and delete Pantries and their contents without writing code.
• Automatic Data Persistence: Data stored in Pantries is automatically saved and available across sessions, eliminating manual database setup.
• Designed for Prototyping: Optimized for quick setup and iteration, making it suitable for proof-of-concept applications and MVPs.
• Serverless Backend Compatibility: Easily integrate with serverless functions (e.g., AWS Lambda, Google Cloud Functions) to provide persistent storage.

Pricing

Pantry offers a free tier and a paid Pro Plan, structured around the number of "Pantries" a user can create. The pricing detailed below is current as of May 2026. For the most up-to-date information, refer to the Pantry pricing page.

Common integrations

• Frontend JavaScript Applications: Directly interact with Pantry's REST API from web browsers using fetch or Axios to store and retrieve dynamic content for static sites or Single Page Applications (SPAs).
• Serverless Functions: Use Pantry as a lightweight data store for AWS Lambda, Google Cloud Functions, or Azure Functions, enabling serverless backends without managing a database. The AWS Lambda developer guide provides context on serverless function development.
• Python Scripts: Integrate into Python applications for data logging, configuration storage, or simple content management using libraries like requests.
• IoT Devices: Store sensor readings or device states from Internet of Things (IoT) devices that can make HTTP requests.
• Mobile App Prototypes: Provide a quick backend for mobile app development, allowing rapid iteration on data models and persistent storage.
• Command-Line Tools: Build simple CLI tools that need to persist small pieces of configuration or state using HTTP requests.

Alternatives

• Firebase Firestore: A NoSQL document database offered by Google, providing real-time data synchronization, offline support, and client-side SDKs, suitable for scalable web and mobile applications.
• Supabase: An open-source Firebase alternative providing a PostgreSQL database, real-time subscriptions, authentication, and storage, often used for full-stack application development.
• JSONPlaceholder: A free fake REST API for testing and prototyping, offering predefined routes and data but without persistent storage – data resets, unlike Pantry.
• AWS DynamoDB: A fully managed NoSQL database service from Amazon Web Services, offering single-digit millisecond performance at any scale, suitable for high-performance applications.
• Google Cloud Datastore: A highly scalable NoSQL document database for web and mobile applications, providing ACID transactions and SQL-like queries.

Getting started

To get started with Pantry, you typically create a new "Pantry" through their web interface, which will give you a unique Pantry ID. Once you have this ID, you can interact with your Pantry using its REST API. The following example demonstrates how to create and retrieve a JSON object (a "basket") using curl, a common command-line tool for making HTTP requests.

First, create a new JSON object in a basket named my-item within your Pantry:

# Replace YOUR_PANTRY_ID with your actual Pantry ID
# This creates a "basket" named 'my-item' with some data
curl -X POST -H "Content-Type: application/json" \
     -d '{"name": "Example Widget", "price": 29.99, "available": true}' \
     https://pantry.cloud/apiv1/pantry/YOUR_PANTRY_ID/basket/my-item

Next, retrieve the JSON object you just created:

# Replace YOUR_PANTRY_ID with your actual Pantry ID
# This retrieves the content of the 'my-item' basket
curl https://pantry.cloud/apiv1/pantry/YOUR_PANTRY_ID/basket/my-item

The response from the GET request will be the JSON data you stored:

{
  "name": "Example Widget",
  "price": 29.99,
  "available": true
}

You can also update an existing basket using a PUT request:

# Replace YOUR_PANTRY_ID with your actual Pantry ID
# This updates the content of the 'my-item' basket
curl -X PUT -H "Content-Type: application/json" \
     -d '{"name": "Updated Widget", "price": 34.50, "available": false}' \
     https://pantry.cloud/apiv1/pantry/YOUR_PANTRY_ID/basket/my-item

And finally, delete a basket:

# Replace YOUR_PANTRY_ID with your actual Pantry ID
# This deletes the 'my-item' basket
curl -X DELETE https://pantry.cloud/apiv1/pantry/YOUR_PANTRY_ID/basket/my-item

This sequence demonstrates the fundamental operations for interacting with Pantry, allowing developers to quickly integrate data storage into their applications with minimal setup, as detailed in the Pantry developer documentation.