ConFlowIO

Product information (PIM)

Pimcore

Reading goes through Pimcore's Datahub, in full or only the objects changed since the last run. Because every Pimcore installation has its own data model, you set in the building block which class is read, which fields and which data model they flow into.

With the Commerce Bundle as the target, products go into every shop with the same mapping.

Demo on your own data

On request a run reads only the objects changed since the last run.

  1. PimcoreProduct information (PIM)
  2. ConFlowIOintegration platformRun active
  3. Shopware 6
  4. Shopify
  5. Adobe Commerce
  • 2ready-made building blocks
  • 21data models in the Commerce Bundle, one mapping for every target

Building blocks

Two building blocks for Pimcore

  • Read

    Reads product data, categories and assets through the Datahub into a freely chosen data model, in full or changes only. Images are passed on as addresses and fetched by the shop itself.

  • Free request

    For anything without a ready-made building block: a request to the API, using the stored credentials.

In practice

A workflow with Pimcore

  1. Product data from the PIM

    The PIM maintains, the shop displays — with no export file in between.

    1. Triggera schedule
    2. ReadPimcore, changes only
    3. Maponto the Commerce Bundle
    4. WriteShopware 6, Shopify or another shop

    A second shop is one more target building block; the mapping stays the same.

Good to know

What to know about Pimcore

  • PrerequisitesWhat has to be set up on your side.
    • Pimcore's Datahub
    • A GraphQL interface set up there
  • Not coveredWhat the integration deliberately does not do.
    • The integration reads; there is no writing building block for Pimcore
    • The integration imposes no data model — you set which class and which fields are read
    • Images are passed on as addresses and fetched by the shop itself, not transferred
  • DurabilityApplies to this integration as to every workflow in ConFlowIO.
    • Failed steps retry themselves
    • Large reads are processed page by page, each page a step of its own
    • A failed run is continued rather than started over
    • Live logs per step, with credentials removed

Contact

See Pimcore on your own data

We are glad to show ConFlowIO on your own data. Bring a real slice of your catalogue.

The difference shows at real volumes — not at five sample records.

Would you like to read our whitepaper? Just say so in your enquiry and we will send it to you.

Rather write directly?info@conflowio.com