Is GraphDB best for automating supply chain functions?

I would like to know is GraphDB good option to create platform on automating supply chain functions like Procure-to-Pay as all documents within the process has highly connected data like purchase order number which ties up with all other document.

Appreciate your valuable input on this?

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Hi @tshaikh :smile:

You wrote GraphDB, but I can only answer in the context of Memgraph or graph databases in general as I haven’t used GraphDB.

The use case seems very suited to be represented and handled as a graph. All the connections between documents, stakeholders and supply chain links can be easily modeled as a graph. It would also be very easy and computationally efficient to find connections to other documents in the network.

You can also use some built-in features to help automate the process. For example, triggers and query modules:

  • Triggers can be used to define events on which a procedure will be triggered. For example, if you need to notify a person about a document once it’s created and added to the database, you can create a trigger that will fire every time a specific document is created and send a notification (email, push notification, etc.) to the person responsible for it or all users who are connected to the document in the database.
  • Query modules can be used to create custom procedures and you can implement them in Python, C/C++ and Rust. For example, you can create the aforementioned notification procedure using query modules. It could be a simple Python script that sends an email to the specified email address.

Also, depending on the architecture of your system, if you are using a message broker like Apache Kafka, you can connect it directly to Memgraph and ingest the data instead of having to implement an intermediary service that would instead connect to the database.

I hope that this info can be of help to you. Feel free to ping me if you have any further questions or you need more info :slight_smile:

Hi Ivan,

Thanks for the detailed explaination and confirming that we can use graph database for supply chain.

I’m looking for confirmation for general graph database and not specific to GraphDB, thanks for clarifying the same :slight_smile:

We are also looking for 100% open source graph db so that we can scale it in future based on our knowledge extraction platform for supply chain, which graph db you recommend to meet our objective.

Many Thanks,

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First of all, I would probably skip GraphDB and other triple stores as they are more suited for semantic web applications. Here you can find a pretty good explanation about the differences between graph databases and RDF stores.

I would recommend you look into Neo4j and Memgraph for your use case. More specific recommendations depend on other requirements your system might have.

  • While the free community version of Neo4j is open-source, it doesn’t include their Graph Data Science library which contains graph algorithms and other utilities. You would have to make an inquiry about an Enterprise license.
  • The free Memgraph community version includes the MAGE graph library and is an open-source project under the Apache 2.0 license.

It’s also worth considering the technology stack you will be using. Neo4j is implemented in Java and custom procedures have to be implemented in Java as well. Memgraph is extendible with procedures written in Python, C/C++, Rust and any other language that can be compiled to a shared library.