Datahub makes headless data delivery in Pimcore even better

Open Source data delivery and data consumption platform provides CaaS via GraphQL

In our video, you can see an early experimental preview of Pimcore Datahub. It will become the main platform for data delivery and data consumption in Pimcore, including:

• Integrating different input and output channel technologies in a simple and easy-to-configure user interface
• Importing and exporting data from and into Pimcore in different formats
• Automated, reusable data pipelines for scale and efficiency

This framework is fully based on Pimcore APIs for superior connectivity. It fosters standard connectors with eCommerce software and SaaS applications. Soon, this hub will also be made compatible with recurring CSV and Microsoft Excel flat file imports and exports. Pimcore Datahub will become the universal tool for getting data in and out of the Pimcore platform, whatever the industry standard, proprietary, or legacy formats. It is deployable anywhere— on-premise, private, and managed cloud services.

Headless Content Management

One exemplary use case of Pimcore Datahub, which can also be seen in our demo video, is its headless CMS feature while using Pimcore for Content-as-a-Service. In many enterprises, only certain parts of centrally managed content or data are needed for new channels such as apps. Datahub makes it possible to manage and provide content data in structured, neutral formats without layout for use in multiple channels.

What About GraphQL?

GraphQL is a query language for APIs. It is designed to fulfill queries with your existing data providing a complete and understandable description of the data in your API. After sending a GraphQL query to your API endpoint, you will get exactly what you need, since GraphQL returns completely predictable results. As a result, you can create fast, stable, and reliable apps. Combine many resources in a single request, since a GraphQL query accesses not just the properties of one resource but also relations between them. This is also the huge difference between REST and GraphQL: while the former requires loading from multiple URLs, the latter gets all the necessary data in a single request. This makes apps using GraphQL lightning fast.

To start learning GraphQL, follow these links:

• Introduction to GraphQL
• GraphQL Community Resources

Partner and Developer Community

We are proud of the Pimcore community project with currently 196 contributors, all source code and development published transparently on GitHub. Pimcore Datahub is a community project, so please contribute and provide your valuable contributions and feedback. The GraphQL channel currently supports 70% of data types of the data objects and all digital assets including their metadata are supported.

If you would like to contribute new data types, please write us directly or directly make a pull request which will be reviewed by our core development team. Any frontend use case implementations will be highly appreciated, so please share them with us.

Pimcore Datahub is a huge topic for the whole community and was one of the most wished features. We love and praise our community! That's why we are very passionate about it.

Your contribution to this open-source project is warmly appreciated.

Coming Next

We are progressing fast. Currently working on support for additional mutations and transformations. Recurring CSV and Microsoft Excel flat file exports will come next. Write access to enable imports will also follow. Pimcore Datahub is still an experimental product extension and available for download as a bundle. Once it is fully ready and in production, it will be merged into our core product.

Get started and have a look at Pimcore Datahub on GitHub.

Or check out some examples of Datahub in our public demo.

• demo.pimcore.com/en/More-Stuff/Demo-Features/Data-Hub (This page shows examples of Datahub queries for product data)
• demo.pimcore.com/en/Events (This page is based on vuejs+apollo which calls Datahub' API to fetch events data from Pimcore)

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