The benefits of graph databases in relation to supply chain transparency
20 September 2016
Graph databases have the ability to model and store data, as well as query both relationships and data. Traditional SQL databases and most NoSQL databases don’t handle this element of data relationships well
Today’s food supply chains are vast and wide-ranging. That’s great, as it means we can put fresh food on the table year-round.
But it also makes them fertile ground for fraud, contamination, insecure production sites and unknown product sources – to name just a few of the problems consumers and producers alike face.
In Europe alone, authorities have had to remove 10,000 tonnes of fake food and an astonishing million litres of unhealthy drink out of our global supply chain in the first three months of 2016 alone.
To quote Interpol , such tampering is now a “a multi-billion criminal industry which can pose serious potential health risks to unsuspecting customers”.
This is a serious issue involving dangerous criminality that can and does endanger life.
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The meat adulteration scandal of 2013, where horse meat was being discovered in various packaged meals wrongly labelled as beef, is just one of many scandals that underscore the need to have precise information about the products being used to create the finished product, by all participants in the supply chain.
We think systems like that are the only way to reduce fraud, reveal unsafe facilities, and have better information leading to stronger consumer trust.
Most brands only know their direct suppliers, with poor visibility into the sub-contractors working for their manufacturers.
In response, we decided to build a collaborative platform to address the issue of transparency in the supply chain.
The result is a software that helps discover, analyse and monitor all suppliers, ingredients and facilities in their entire supply chain.
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The platform includes detailed information about all elements in the supply chain (products, suppliers, etc.