Posts

5 Reasons to Choose a Graphical JSON Schema Editor


The advantages of JSON as a lightweight, interoperable data format have secured its place as a favored mechanism for serializing and transporting data on the web. However, most applications still benefit from or require validation of client-submitted data. Enter the JSON Schema spec, which lets you describe the structure of JSON data for a particular application, for both documentation and validation purposes.

Though JSON Schema code is by design human-readable, building a complex schema with nested and repeating sections in a text-only editor becomes time consuming and error-prone quickly. Let’s look at five ways a graphical editor is a must-have for JSON Schema development.

JSON Schema Editor in XMLSpy
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Updated JSON Schema Support Highlights v2019 Release 3


From updated support for standards and relational databases to several new data mapping options, Altova’s Version 2019 Release 3 product line addresses developer requests and ups the ante with innovative new functionality. Let’s take a look at the highlights.

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An Easy Way to Test HTTP Requests During Development


Web and web services developers often need to send HTTP requests – whether for testing APIs, testing REST and SOAP web services, or managing web sites.

XMLSpy now makes it easy to send and receive HTTP requests directly in the XML editor during development with a new HTTP Window and WADL/WSDL Import Wizard.

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The Only JSON Dev Tool You’ll Need


While XMLSpy might not be the first tool developers think of when they’ve got a JSON development task, XMLSpy includes comprehensive support for working with JSON, JSON Schema, and related technologies.

Over the past few product releases, we’ve added intelligent functionality for editing and converting JSON and JSON5 data to the product. We’ve completed the circle with one-click conversion between XML Schemas and JSON Schemas, as well as sample instance generation and JSON Schema documentation generation. And, most recently, we’ve added support for processing JSON with XSLT,  XPath, and XQuery.

Let’s walk through some common examples demonstrating this functionality – and see how these time-saving tools make XMLSpy the only JSON development tool you’ll need.

Developer using JSON tool

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Top Five Features in Altova’s Latest Release


Release 2 of the Altova Version 2018 product line introduces a host of new features and updates, and even a brand-new product.

Let’s take a look at the top five reasons you won’t want to wait to download this version.

News about Version 2018 R2

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Support for JSON5 in Altova MissionKit, Server Products, and MobileTogether


Altova products have supported JSON for several years. Now, Version 2017 Release 3 of MissionKit and Server products, and MobileTogether Version 3.2 all include support for JSON5 across the product line.

The JSON data format was originally designed to be machine-written and consumed, promoting efficient communication between servers. Usage has expanded and JSON5 is a proposed extension intended to make JSON code easier for humans to write and read.  JSON5 extends JSON by adding some ECMAScript 5 features and, like JSON, is a strict subset of JavaScript. Specifically, JSON5 permits inline and block comments, allows long strings to be split over several lines, and defines alternate legal syntax options for quotes and commas.  These features are not permitted in standard JSON, so files containing the proposed enhancements are typically identified with the .json5 filename suffix.

This post details specific support for JSON5 in each Altova product.

Learn about JSON5 support in Altova tools

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JSON Data Mapping and Transformation with MapForce


JSON is a popular format for transferring data between systems thanks to its simple markup, small footprint, and heritage based on the JavaScript programming language. MapForce supports JSON as both an input and output format for JSON data mapping and transformation. For instance, MapForce can extract information from any popular database and produce a JSON file ready for transfer.
The Requirement: Here is an example of a typical need for JSON data mapping: A manufacturing company controls costs by exploiting a just-in-time assembly process with very little parts inventory on hand. New customer orders are logged in a sales database, and at the end of every day the components needed to assemble that day’s sales are tabulated via a query into the database. The required parts will be ordered from suppliers via a purchase order transferred in JSON format.

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