A simple, self-contained, serverless, zero-configuration JSON document store that sandboxes the current working directory like SQLite.
JSONlite is a simple, self-contained, serverless JSON document store that operates by sandboxing the current working directory, similar to how SQLite works. It allows users to store, retrieve, and manage JSON documents locally without any configuration or running a separate server. The tool validates JSON and saves each document as a UUID-named file, making it ideal for lightweight data persistence in scripts and development environments.
Developers and scripters who need a minimal, zero-configuration way to persist JSON data locally without setting up a database server. It's particularly useful for CLI tooling, local development prototypes, and automation scripts.
JSONlite stands out for its extreme simplicity and lack of dependencies—it requires only bash and a JSON formatter to run. Unlike heavier database solutions, it offers instant setup, no server management, and a straightforward CLI interface, making it the fastest way to add JSON storage to any project.
A simple, self-contained, serverless, zero-configuration, json document store.
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Works instantly with default data directory, customizable via JSONLITE_DATA_DIR environment variable, eliminating setup overhead as per the Configuration section.
Runs entirely in the local directory without a background process, making it ideal for scripts and local development, aligning with its self-contained philosophy.
Requires only bash, uuidgen, and a JSON formatter (like json_reformat or jq), with no external server or complex libraries needed.
Validates all stored JSON using tools such as json_reformat or jq, ensuring data integrity before saving documents as UUID-named files.
Offers simple set, get, count, delete, and drop operations with piping and file input support, documented clearly in the API section.
Speed heavily depends on the JSON formatter choice, with python -m json.tool being slow (28s for 1k documents), and it's not optimized for high-throughput scenarios.
Only supports document retrieval by UUID, lacking features like searching, filtering, or indexing within JSON content, which restricts use cases.
Stores data as individual files in a directory, leading to potential scalability issues with large document counts and no support for distributed environments.
Requires a Unix-like environment with bash and standard tools, making it less suitable for Windows without additional setup or emulation.