Large JSON data solution

The usual JSON Schema validator implementations and JSON editor environments are working fine for JSON input if the size does not exceed a couple of MBs. But what if you need to process and validate JSON text of several 100 MB or even GB of size? You need a tool that enables you to validate large JSON content and browse and locate error positions in your data.

The streaming JSON validator available in the Large Data edition is loading and processing JSON input data in full streaming mode. This results in constant memory usage during validation and supports checking JSON text of almost any size.

To get an idea of what the JSONBuddy Large Data package can do, here is a list of options for a typical workflow:

1. Large JSON text is often minified. JSONBuddy allows formatting (prettify) JSON input of any size when used from the built-in File Explorer window for improved readability. A formatted copy will be saved next to the original JSON input.
2. In general, the following commands are working in streaming mode using the File Explorer window: Check JSON well-formed, pretty-print and remove whitespace.
3. Is your data using a legacy format like CSV? Use the tool to convert from CSV into JSON content.
4. Validate big JSON data using the streaming JSON validator with full support for draft-07.
5. Get a detailed error report as XML for further transformation/publication. XML can be easily transformed into HTML.
6. Use JSONBuddy and the built-in JSONPointer evaluator to locate any error position. The streaming JSON validator provides error locations as JSONPointer paths.
7. Open, browse and edit large JSON in JSONBuddy Plus.
8. Resolve a JSONPointer from any position in the JSON text.

• Command-line tool (CLI). Integrate the JSON Schema validator in batch and server tasks.
• JSONBuddy Plus. Complete JSON editor environment for general testing, JSON Schema design as well as browse and edit big JSON content.

Basic performance measurements As approximate value, 100 MB of JSON text can be validated in less than one minute using the performance of a mid-range hardware configuration. Memory footprint is constant for a typical validation check. Larger input size is mainly limited by processing time.

You need to validate and process large JSON text?
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