Think of the cloud as a reservoir and the edge as water storage tanks. The reservoir is a central area that collects large amounts of water, while storage tanks sit in every apartment building.

The reservoir supplies water to tanks, which then provides water to homes. This allows citizens almost immediate access to water. If water had to travel from the reservoirs to homes every time someone switched on a faucet, residents would have to wait a long time before water starts flowing.

Data works the same way. When data is closer to citizens, they can access it more quickly. Balachandar Seetharaman, Principal Solution Engineer at Yugabyte, shares how cities can choose the right database to bring data closer to their citizens.

Why smart cities need data close by

Data powers the many technologies smart cities need to run. For example, cities examine how citizens are using utilities to improve their services, says Balachandar.

A smart district in Singapore uses sensors to gather data on how many people are waiting at a lift lobby. If the sensors detect more people, the building will dispatch more lift cars, wrote GovInsider.

In Thailand, Phuket uses wristbands to track the locations of tourists going out to sea. This information is used to ensure that visiting divers don’t drift too far from their boats for their safety, GovInsider reported.

Such tech relies on near real-time data to function, meaning that data needs to be close by. Cities can ensure this by storing their data on the edge – at ‘storage tanks’ near to citizens.

Fetching data from the cloud takes more time as compared to fetching data from the edge, explains Balachandar. This may cause lag time in the tech citizens use.

For example, citizens may want to get real-time information on vacant lots in a carpark. If there is a delay in sensors receiving that data, empty lots may be taken up before citizens even receive the information.

Choosing the right database for the job

But bringing data closer to citizens comes with challenges.

Firstly, governments need to ensure that tech continues to run even if databases fail.

This is where distributed databases like YugabyteDB come in. A central database is like one large reservoir. If the reservoir is empty, all tanks in the city will not receive water. On the other hand, distributed databases can be seen as multiple smaller reservoirs. If one reservoir is empty, tanks can simply draw from another.

Distributed databases ensure that data is always available. They replicate data across different regions or zones in a city. If there is a power outage in one area, tech can draw data from elsewhere. This ensures that citizens don’t feel the outage, keeping them happy, says Balachandar.

Internet service provider Plume, for example, uses YugabyteDB to ensure that they can keep smart homes running at all times. With YugabyteDB, Plume does not lose any data even when there is any failover. Additionally, YugabyteDB ensures organisations can restore function in merely three seconds if failures do occur.

Another challenge governments face is the need to increase their data capacity. A city may have a population of X today, but it may become X plus Y later on, says Balachandar. Then, data capacity needs to be upgraded as well, he adds.

Having a distributed database ensures that cities can scale their data capacity easily when needed, highlights Balachandar.

Upgrading a central database requires expanding its physical infrastructure. This can lead to downtime while data is being transferred to a larger data centre. Having a distributed database means that when one location is upgrading, tech can scale horizontally and distribute the data without impacting existing database nodes in the city.

Processing data even if the shoe doesn’t fit

Distributed databases are also ideal for smart cities as they are able to process different types of data easily. Smart devices within a city can come from many different manufacturers, and collect various types of data.

Such unstructured data is difficult for traditional databases to process as they do not follow a fixed format. Traditional databases may need to reformat or filter these data types before analysing them, which increases lag time.

Distributed databases like YugabyteDB are able to support both structured and unstructured data. They do so by collecting and storing all incoming data rather than filtering them at the onset.

Subsequently, smart devices can draw only the data they need from the database – “no processing time needed,” highlights Balachandar. “This way, cities will not lose any time in providing services to citizens,” he says.

Much like how water is a necessary resource for any city’s survival, data is the lifeblood of a smart city. For smart cities to thrive, governments need to make sure data is constantly flowing. Distributed databases can help them ensure this.

Find out how databases have evolved over the years at ‘The Database Evolution (From Relational to NoSQL to NewSQL for Cloud Native Applications’ webinar, happening on 27 May 2022. Register for the webinar here.