How the Graph is Driving Tech City Start-ups
Jim Webber, Chief Scientist at Neo Technology takes a look at London’s burgeoning tech start-up scene and the way they are using the world’s largest graph database community to come to terms with big data.
Chasing San Francisco and New York, London now hosts the third largest technology start-up cluster in the world and the biggest in Europe. To encourage this growth, the UK Government has proposed a significant amount of funding within this area and earlier this week Buckingham Palace hosted a reception to highlight the growing contribution of the start-up community to the UK economy.
However, equally as important as the Government’s continued investment in Tech City is the growing strength of London’s overall developer community. Essential to the survival of any start-up tech scene, a large and well-connected developer community can offer companies access to the wide range of technical expertise they need in order to make their mark and lead cutting-edge innovation projects. Additionally, this pool of talent can help spark new ideas and creativity within some of the more established businesses in the region, as they face stiff competition from their new rivals.
Fortunately, for London’s tech start-ups, the developer community is flourishing and – particularly satisfying for my own company, Neo Technology – is also host to the largest graph database community in the world with well over a thousand developersand growing! Graph databases differ from the traditional relational model of data storage and analysis (which holds all data in tables – similar to a spreadsheet) and instead allow businesses to make better sense of the relationships within very complex data. Graphs allow organisations to ask complicated, abstract questions such as: ‘How many times has my viral game been shared on social media and who is recommending it to whom?’ or ‘what is the quickest route from A to B?’. It’s this sort of database which sits behind social networking (such as Facebook and Twitter) where it’s important to track who knows who, their shared ‘likes’ and their common interests.