Lessons We Can All Learn from the Sharing Economy

Companies in the sharing economy are creating superior experiences for their customers with the aid of massive databases engineered on a global scale.

Guest Commentary, Guest Commentary

March 18, 2019

6 Min Read

Every generation has its gold rush, and it’s clear that the next gold rush is the sharing economy. According to a McKinsey report, more than 150 million people in the US and Europe are providers on some sort of sharing platform. At the same time, incredible momentum is pushing both Uber and Lyft to billion-dollar IPOs in 2019. But we haven’t seen anything concrete yet. There is huge potential for even more growth as the sharing economy gains footholds in emerging markets in Asia, Africa and Latin America. In fact, PwC estimates that the global sharing economy will reach $335 billion by 2025, mainly due to growth in these geographies. 

Sharing platforms will need to act fast in this competitive market. Both merchants and users are especially loyal in the sharing economy, often seeing themselves as part of a tight-knit community. Once they get set up, it’s really hard to get them to move to a competing platform. As a result, there’s a huge battle going on to onboard users as quickly as possible in these emerging markets. Stickiness will be important, and whoever is able to provide a unique and consistent experience for an exploding customer base will be primed to carve out market share. 

Database Architects will be the Unsung Heroes

Platforms need to onboard and authenticate millions of users across the globe by collecting a massive amount of data such as names, addresses, title information, social security numbers and payment information, and do it in real time. We’re not just talking about a single merchant selling to millions of users. The sharing economy enables anonymous transactions among millions of merchants and millions of users. Platforms need to ensure people are who they say they are, and they have the right to share a piece of equipment or property.

The way data is stored and shared across a global network of databases and cloud infrastructure will enable the kind of massive growth that will be required. It will allow platforms to deploy and expand so much faster and keep up with complex and dynamic compliance and cybersecurity requirements. It’s clear that traditional SQL databases are not up to the task, so a new kind of database platform, like those offered by Couchbase and other NoSQL databases, will be needed to keep up with the massive growth and scalability requirements of the sharing economy.

Rather than rely on SQL — a technology that is outdated and difficult to scale — organizations should reengineer their underlying database technology using open-source and NoSQL technologies to better meet today’s demanding growth and scalability needs. 

At Yapstone we leverage Couchbase’s technologies, which allows our platform to onboard and authenticate users in real time, ensure availability on a global scale and enable a multi-tenant architecture that can spin up microservices to customers on demand and meet various compliance requirements across diverse geographies and industries.

Lessons Learned from the Sharing Economy

The sharing economy is just the vanguard of industries that will need new ways of storing and managing mountains of information spread out across cloud infrastructures. Soon, barriers to all markets will be broken down, and we’ll truly have 7 billion people participating in a global economy. In order for that to happen, companies will need to learn from how the winners in the sharing economy are able to quickly on board users and provide them with a reliable and consistent experience no matter where they log on from. 

Here are three best practices that companies can learn from the sharing economy as it relates to database growth and scalability:

Keep data close to memory in the computer architecture. The more data that is stored in a database, the harder it is to recall that information quickly when it is needed. New data essentially gets swallowed up, and the user is forced to wait to query the appropriate database, resulting in a degradation of performance as the platform scales. This is a problem for the sharing economy and any rapidly-growing industry where stickiness can make a big difference when trying to gobble up valuable market share.

The experience for the first customer needs to be the same as the 1 millionth customer and beyond. Organizations can solve this problem by incorporating a database architecture that provides very fast memory-to-memory replication of data sitting in the NoSQL engine. This memory and network centric approach provides a high-performance replication backbone that allows new workloads to be added easily while maintaining performance at scale.

Build geographic distribution and instant data replication into your architecture. All business will eventually be global. Everyone from fishermen in Southeast Asia to entrepreneurs in Africa will be interconnected, using massive platforms to move goods, services and ideas on a global scale. It’s important that performance and underlying data is consistent between geographies and that these platforms never go down. Small problems in one region can affect markets halfway around the world like small ripples that get stronger as they spread out from the center. Also, data generated or input as master data in one region could be needed instantly in another region. To combat this, organizations should rely on a database platform that is distributed across data centers around the world and also support instant low-latency bi-directional data replication, providing critical redundancy and high availability of data. If disaster strikes in one area, workloads can be seamlessly migrated to a nearby data center without operations going down.

Enable elastic scaling. Demand changes as markets ebb and flow, crops yield record years and the sun sets over the ocean. Database infrastructure needs to scale up and down with this demand, ensuring that performance and availability is consistent at all times without having to over-provision resources. Employing an elastic scaling to autonomously manage database infrastructure allows organizations to quickly spin up and scale back microservices and performance at will. This allows Yapstone to constantly innovate and add new services that meet dynamic demand without having to worry about whether its infrastructure can handle the stress. Everything is done automatically to ensure transaction services are up and running optimally and securely at all times.

The sharing economy is a harbinger of how the global economy will evolve. As Uber and Lyft and HomeAway and AirBnB fight over a rapidly growing market share, the rest of the business world should take notice. They need to understand how these companies are creating superior and consistent experiences for their customers and learn the way these companies’ massive databases are engineered on a global scale in such a way to enable growth and scalability.

Sanjay Saraf is Chief Technology Officer at Yapstone.

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Guest Commentary

Guest Commentary

The InformationWeek community brings together IT practitioners and industry experts with IT advice, education, and opinions. We strive to highlight technology executives and subject matter experts and use their knowledge and experiences to help our audience of IT professionals in a meaningful way. We publish Guest Commentaries from IT practitioners, industry analysts, technology evangelists, and researchers in the field. We are focusing on four main topics: cloud computing; DevOps; data and analytics; and IT leadership and career development. We aim to offer objective, practical advice to our audience on those topics from people who have deep experience in these topics and know the ropes. Guest Commentaries must be vendor neutral. We don't publish articles that promote the writer's company or product.

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